2023推荐系统论文集锦

2023-12-20 15:31:46

WSDM 2024

Defense Against Model Extraction Attacks on Recommender Systems
Sixiao Zhang (Nanyang Technological University)*; Hongzhi Yin (The University of Queensland); Hongxu Chen (The University of Queensland); Cheng Long (Nanyang Technological University)

Motif-based Prompt Learning for Universal Cross-domain Recommendation
Bowen Hao (Captial Normal University)*; Chaoqun Yang (Griffith University); Lei Guo (Shandong Normal University); Junliang Yu (The University of Queesland); Hongzhi Yin (The University of Queensland)

To Copy, or not to Copy; That is a Critical Issue of the Output Softmax Layer in Neural Sequential Recommenders
Haw-shiuan Chang (Amazon)*; Nikhil Agarwal (Amazon.com); Andrew McCallum (Univ of Massachusetts Amherst)

Linear Recurrent Units for Sequential Recommendation
Zhenrui Yue (University of Illinois Urbana-Champaign); Yueqi Wang (University of California, Berkeley); Zhankui He (UC, San Diego)*; Huimin Zeng (University of Illinois at Urbana-Champaign); Julian McAuley (UCSD); Dong Wang (University of Illinois Urbana-Champaign)

User Behavior Enriched Temporal Knowledge Graph for Sequential Recommendation
Hengchang Hu (National University of Singapore)*; Wei Guo (Huawei Noah’s Ark Lab); Xu Liu (National University of Singapore); Yong Liu (Huawei); Ruiming Tang (Huawei Noah’s Ark Lab); Rui Zhang (ruizhang.info); Min-Yen Kan (National University of Singapore)

Intent Contrastive Learning with Cross Subsequences for Sequential Recommendation
Xiuyuan Qin (Soochow University)*; Huanhuan Yuan (Soochow University); Pengpeng Zhao (Soochow University); Guanfeng Liu (Macquarie University); Fuzhen Zhuang (Institute of Artificial Intelligence, Beihang University); Victor S. Sheng (Texas Tech University)

Budgeted Embedding Table For Recommender Systems
Yunke Qu (The University of Queensland)*; Tong Chen (The University of Queensland); Quoc Viet Hung Nguyen (Griffith University); Hongzhi Yin (The University of Queensland)

Pre-trained Recommender Systems: A Causal Debiasing Perspective
Ziqian Lin (University of Wisconsin–Madison)*; Hao Ding (AWS AI Lab); Nghia Trong Hoang (Washington State University); Branislav Kveton (AWS AI Labs); Anoop Deoras (Amazon); Hao Wang (Rutgers University)

Dynamic Sparse Learning: A Novel Paradigm for Efficient Recommendation
Shuyao Wang (University of Science and Technology of China)*; Yongduo Sui (University of Science and Technology of China); Jiancan Wu (University of Science and Technology of China); Zhi Zheng (University of Science and Technology of China); Hui Xiong (Hong Kong University of Science and Tech)

PEACE: Prototype lEarning Augmented transferable framework for Cross-domain rEcommendation
Chunjing Gan (Ant Group)*; Bo Huang (Ant Group); Binbin Hu (Ant Group); Jian Ma (Ant Group); Zhiqiang Zhang (Ant Group); Jun Zhou (Ant Financial); Guannan Zhang (Ant Group); WENLIANG ZHONG (Ant Group)

MADM: A Model-agnostic Denoising Module for Graph-based Social Recommendation
Wenze Ma (Shanghai Jiao Tong University)*; Yuexian Wang (Shanghai Jiao Tong University); Yanmin Zhu (Shanghai Jiao Tong University); Zhaobo Wang (Shanghai Jiao Tong University); Mengyuan Jing (Shanghai Jiao Tong University); Xuhao Zhao (Shanghai Jiao Tong University); Jiadi Yu (Shanghai Jiao Tong University); Feilong Tang (Shanghai Jiao Tong University)

Collaboration and Transition: Distilling Item Transitions into Multi-Query Self-Attention for Sequential Recommendation
Tianyu Zhu (University of Montreal)*; Yansong Shi (Tsinghua University); Yuan Zhang (Kuaishou Inc.); Yihong Wu (Université de Montréal); Fengran Mo (Université de Montréal); Jian-Yun Nie (Université de Montréal)

CDRNP: Cross-Domain Recommendation to Cold-Start Users via Neural Process
Xiaodong Li (Institute of Information Engineering, Chinese Academy of Sciences)*; Jiawei Sheng ( Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China); Jiangxia Cao (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China); Tingwen Liu (Institute of Information Engineering, CAS); Wenyuan Zhang (Institute of Information Engineering, Chinese Academy of Sciences); Quangang Li (Institute of Information Engineering, CAS)

Inverse Learning with Extremely Sparse Feedback for Recommendation
Guanyu Lin (Carnegie Mellon University)*; Chen Gao (Tsinghua University); Yu Zheng (Tsinghua University); Yinfeng Li (Kuaishou Inc); Jianxin Chang (Kuaishou Inc); Yanan Niu (Kuaishou Inc); Yang Song (Kuaishou Technology); Kun Gai (AI); Zhiheng Li (Tsinghua University); Depeng Jin (Tsinghua University); Yong Li (Tsinghua University)

Contextual MAB Oriented Embedding Denoising for Sequential Recommendation
Zhichao Feng (Beijing University of Post and Telecommunications); Pengfei Wang (School of Computer Science, Beijing University of Posts and Telecommunications)*; Kaiyuan Li (Beijing University of Posts and Telecommunications); Chenliang Li (Wuhan University); Shangguang Wang (State Key Laboratory of Networking and Switching Technology)

Mixed Attention Network for Cross-domain Sequential Recommendation
Guanyu Lin (Carnegie Mellon University)*; Chen Gao (Tsinghua University); Yu Zheng (Tsinghua University); Jianxin Chang (Kuaishou Inc); Yanan Niu (Kuaishou Inc); Yang Song (Kuaishou Technology); Kun Gai (AI); Zhiheng Li (Tsinghua University ); Depeng Jin (Tsinghua University); Yong Li (Tsinghua University); Meng Wang (Institute of Artificial Intelligence, Hefei Comprehensive National Science Center)

Knowledge Graph Context-Enhanced Diversified Recommendation
Xiaolong Liu (University of Illinois at Chicago)*; Liangwei Yang (University of Illinois at Chicago); Zhiwei Liu (Salesforce); Mingdai Yang (University of Illinios at Chicago); Chen Wang (University of Illinois at Chicago); Hao Peng (Beihang University); Philip S Yu (UIC)

Exploring Adapter-based Transfer Learning for Recommender Systems: Empirical Studies and Practical Insights
Junchen Fu (Westlake University)*; Fajie Yuan (Westlake University); Yu Song (Westlake University); Zheng Yuan (Westlake University); Mingyue Cheng (University of Science and Technology of China); Shenghui Cheng (Westlake University); Jiaqi Zhang (Westlake University); Jie Wang (Westlake University); Yunzhu Pan (University of Electronic Science and Technology of China)

Diff-MSR: A Diffusion Model Enhanced Paradigm for Cold-Start Multi-Scenario Recommendation
Yuhao Wang (City University of Hong Kong)*; Ziru Liu (City University Of HongKong ); Yichao Wang (Huawei Noah’s Ark Lab); Xiangyu Zhao (City University of Hong Kong); Bo Chen (Huawei Noah’s Ark Lab); Huifeng Guo (Huawei Noah’s Ark Lab); Ruiming Tang (Huawei Noah’s Ark Lab)

AutoPooling: Automated Pooling Search for Multi-valued Features in Recommendations
He Wei (Tencent Inc.)*; Meixi Liu (Machine learning platform department, Tencent TEG); Yang Zhang (Tencent Inc)

C^2DR: Robust Cross-Domain Recommendation based on Causal Disentanglement
Menglin Kong (Central South University); Jia Wang (Xi’an Jiaotong-Liverpool University)*; Yushan Pan (Xi’an Jiaotong-Liverpool University); Haiyang Zhang (Xi’an Jiaotong-Liverpool University); Muzhou Hou (Central South Uinversity)

Unified Pretraining for Recommendation via Task Hypergraphs
Mingdai Yang (University of Illinios at Chicago)*; Zhiwei Liu (Salesforce); Liangwei Yang (University of Illinois at Chicago); Xiaolong Liu (University of Illinois at Chicago); Chen Wang (University of Illinois at Chicago); Hao Peng (Beihang University); Philip S Yu (UIC)

SSLRec: A Self-Supervised Learning Library for Recommendation
Xubin Ren (the University of Hong Kong)*; Lianghao Xia (University of Hong Kong); Yuhao Yang (Wuhan University); Wei Wei (University of Hong Kong); Tianle Wang (HKU); Xuheng Cai (The University of Hong Kong); Chao Huang (University of Hong Kong)

Multi-Sequence Attentive User Representation Learning for Side-information Integrated Sequential Recommendation
Xiaolin Lin (Shenzhen University)*; Jinwei Luo (Shenzhen University); Junwei Pan (Tencent); Weike Pan (Shenzhen University); Zhong Ming (Shenzhen University); Xun Liu (Tencent); HUANG SHUDONG (tencent); Jie Jiang (Tencent Inc.)

LabelCraft: Empowering Short Video Recommendations with Automated Label Crafting
Yimeng Bai (University of Science and Technology of China)*; Yang Zhang (University of Science and Technology of China); Jing Lu (Kuaishou Inc); Jianxin Chang (Kuaishou Inc); Xiaoxue Zang (Kuaishou Inc); Yanan Niu (Kuaishou); Yang Song (Kuaishou Technology); Fuli Feng (University of Science and Technology of China)

MONET: Modality-Embracing Graph Convolutional Network and Target-Aware Attention for Multimedia Recommendation
Yungi Kim (Hanyang University); Taeri Kim (Hanyang University); Won-Yong Shin (Yonsei University, Korea); Sang-Wook Kim (Hanyang University, Korea)*

RecJPQ: Training Large-Catalogue Sequential Recommenders
Aleksandr V Petrov (University of Glasgow)*; Craig Macdonald (University of Glasgow)

On the Effectiveness of Unlearning in Session-Based Recommendation
Xin Xin (Shandong University); Liu Yang (Shandong University)*; Ziqi Zhao (Shandong University); Pengjie Ren (Shandong University); Zhumin Chen (Shandong University); Jun Ma (Shandong University); Zhaochun Ren (Leiden University)

Proxy-based Item Representation for Attribute and Context-aware Recommendation
Jinseok Seol (Seoul National University)*; Minseok Gang (Seoul National University); Sang-goo Lee (Seoul National University); Jaehui Park (University of Seoul)

IncMSR: An Incremental Learning Approach for Multi-Scenario Recommendation
Kexin Zhang (Tsinghua University)*; Yichao Wang (Huawei Noah’s Ark Lab); Xiu Li (Tsinghua University); Ruiming Tang (Huawei Noah’s Ark Lab); Rui Zhang (ruizhang.info)

Deep Evolutional Instant Interest Network for CTR Prediction in Trigger-Induced Recommendation
Zhibo Xiao (Alibaba Group)*; Luwei Yang (Alibaba Group); Tao Zhang (Alibaba Group); Wen Jiang (Alibaba Group); Wei Ning ( Alibaba Group); Yujiu Yang (Tsinghua University)

User Consented Federated Recommender System Against Personalized Attribute Inference Attack
Qi Hu (Hong Kong University of Science and Technology)*; Yangqiu Song (Hong Kong University of Science and Technology)

Neural Kalman Filtering for Robust Temporal Recommendation
Jiafeng Xia (Fudan University)*; Dongsheng Li (Microsoft Research Asia); Hansu Gu (Amazon.com); Tun Lu (Fudan University); Peng Zhang (Fudan University); Li Shang (Fudan University); Ning Gu (Fudan University)

Attribute Simulation for Item Embedding Enhancement in Multi-interest Recommendation
Yaokun Liu (Tianjin University)*; Xiaowang Zhang (Tianjin University); Minghui Zou (Tianjin University); Zhiyong Feng (Tianjin University)

ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models
Qijiong Liu (The Hong Kong Polytechnic University)*; NUO CHEN (Waseda University); Tetsuya Sakai (Waseda University); Xiao-Ming Wu (PolyU Hong Kong)

Debiasing Sequential Recommenders through Distributionally Robust Optimization over System Exposure
Jiyuan Yang (Shandong University)*; Yue Ding (Shanghai Jiao Tong University); YIDAN WANG (SHANDONG UNIVERSITY); Pengjie Ren (Shandong University); Zhumin Chen (Shandong University); Fei Cai (National University of Defense Technology); Jun Ma (Shandong University); Rui Zhang (ruizhang.info); Zhaochun Ren (Leiden University); Xin Xin (Shandong University)

Knowledge Graph Diffusion Model for Recommendation
Yangqin Jiang (University of Hong Kong)*; Yuhao Yang (Wuhan University); Lianghao Xia (University of Hong Kong); Chao Huang (University of Hong Kong)

Large Language Models for Data Aumgnetation in Recommendation
Wei Wei (University of Hong Kong)*; Xubin Ren (the University of Hong Kong); Jiabin Tang (University of Hong Kong); Qinyong Wang (Baidu Inc); Lixin Su (University of Chinese Academy of Sciences); Suqi Cheng (Baidu Inc.); junfeng wang (Baidu); Dawei Yin (Baidu); Chao Huang (University of Hong Kong)

Interact with the Explanations: Causal Debiased Explainable Recommendation System
Xu Liu (Shanghai Jiao Tong University); Tong Yu (Adobe Research); Kaige Xie (Georgia Institute of Technology); Junda Wu (New York University); Shuai Li (Shanghai Jiao Tong University)*

Global Heterogeneous Graph and Target Interest Denoising for Multi-behavior Sequential Recommendation
Xuewei Li (Tianjin University); Hongwei Chen (College of Intelligence and Computing, Tianjin University)*; Jian Yu (Tianjin University); Mankun Zhao (Tianjin University); Tianyi Xu (Tianjin University); Wenbin Zhang (Information and Network Center, Tianjin University); Mei Yu (Tianjin University)

MultiFS: Automated Multi-Scenario Feature Selection in Deep Recommender Systems
Dugang Liu (Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen University)*; Chaohua Yang (Shenzhen University); Xing Tang (Tencent); Yejing Wang (City University of Hongkong); Fuyuan Lyu (McGill University); weihong luo (tencent); Xiuqiang He (Tencent); Zhong Ming (Shenzhen University); Xiangyu Zhao (City University of Hong Kong)

Learning Alignment and Compactness in Collaborative Filtering
Huiyuan Chen (Visa Research)*; Vivian Lai (Visa Research); Hongye Jin (Texas A&M University); Zhimeng Jiang (Texas A&M University); Mahashweta Das (Visa Research); Xia Hu (Rice University)

Calibration-compatible Listwise Distillation of Privileged Features for CTR Prediction
Xiaoqiang Gui (Shandong University)*; Yueyao Cheng (Alibaba Group); Xiang-Rong Sheng (Alibaba Group); Yunfeng Zhao (Shandong University); Guoxian Yu (Shandong University); Shuguang Han (Alibaba Inc.); Yuning Jiang (Alibaba Group); Jian Xu (Alibaba Group); Bo Zheng (Alibaba Group)

Cost-Effective Active Learning for Bid Exploration in Online Advertising
Zixiao Wang (Shanghai Jiao Tong University)*; Zhenzhe Zheng (Shanghai Jiao Tong University); Yanrong Kang (Tencent); Jiani Huang (Shanghai Jiao Tong University)

Pitfalls in Link Prediction with Graph Neural Networks: Understanding the Impact of Target-link Inclusion & Better Practices
Jing Zhu (University of Michigan, Ann Arbor)*; Yuhang Zhou (University of Maryland); Vassilis N. Ioannidis (University of Minnesota); Shengyi Qian (University of Michigan); Wei Ai (University of Maryland); Xiang Song (Amazon AWS); Danai Koutra (U Michigan)

Not All Negatives Are Worth Attending to: Meta-Bootstrapping Negative Sampling Framework for Link Prediction
Yakun Wang (Ant Group)*; Binbin Hu (Ant Group); Shuo Yang (Ant Group); Meiqi Zhu (Ant Group); Zhiqiang Zhang (Ant Group); Qiyang Zhang (Ant Group); Jun Zhou (Ant Financial); Guo Ye (antgroup); HUIMEI HE (antgroup)

SIGIR 2023

1. Poisoning Self-supervised Learning Based Sequential Recommendations

Yanling Wang, Yuchen Liu, Qian Wang, Cong Wang and Chenliang Li

2. M2GNN: Metapath and Multi-interest Aggregated Graph Neural Network for Tag-based Cross-domain Recommendation

Zepeng Huai, Yuji Yang, Mengdi Zhang, Zhongyi Zhang, Yichun Li and Wu Wei

3. EulerNet: Adaptive Feature Interaction Learning via Eulers Formula for CTR Prediction

Zhen Tian, Ting Bai, Wayne Xin Zhao, Ji-Rong Wen and Zhao Cao

4. Continuous Input Embedding Size Search For Recommender Systems

Yunke Qu, Tong Chen, Xiangyu Zhao, Lizhen Cui, Kai Zheng and Hongzhi Yin

5. A Preference Learning Decoupling Framework for User Cold-Start Recommendation

Chunyang Wang, Yanmin Zhu, Aixin Sun, Zhaobo Wang and Ke Wang

6. Prompt Learning for News Recommendation

Zizhuo Zhang and Bang Wang

7. Multi-view Multi-aspect Neural Networks for Next-basket Recommendation

Zhiying Deng, Jianjun Li, Zhiqiang Guo, Wei Liu, Li Zou and Guohui Li

8. Strategy-aware Bundle Recommender System

Yinwei Wei, Xiaohao Liu, Yunshan Ma, Xiang Wang, Liqiang Nie and Tat-Seng Chua

9. Knowledge-enhanced Multi-View Graph Neural Networks for Session-based Recommendation

Qian Chen, Zhiqiang Guo, Jianjun Li and Guohui Li

10. Exploring scenarios of uncertainty about the users preferences in interactive recommendation systems

Ncollas Silva, Thiago Silva, Henrique Hott, Yan Ribeiro, Adriano Pereira and Leonardo Rocha

11. Topic-enhanced Graph Neural Networks for Extraction-based Explainable Recommendation

Jie Shuai, Le Wu, Kun Zhang, Peijie Sun, Richang Hong and Meng Wang

12. Instance Transfer for Cross-Domain Recommendations

Jingtong Gao, Xiangyu Zhao, Bo Chen, Fan Yan, Huifeng Guo and Ruiming Tang

13. EEDN: Enhanced Encoder-Decoder Network with Local and Global Context Learning for POI Recommendation

Xinfeng Wang, Fumiyo Fukumoto, Jin Cui, Yoshimi Suzuki, Jiyi Li and Dongjin Yu

14. Generative-Contrastive Graph Learning for Recommendation

Yonghui Yang, Zhengwei Wu, Le Wu, Kun Zhang, Richang Hong, Zhiqiang Zhang, Jun Zhou and Meng Wang

15. Time-interval Aware Share Recommendation via Bi-directional Continuous Time Dynamic Graphs

Ziwei Zhao, Xi Zhu, Tong Xu, Aakas Lizhiyu, Yu Yu, Xueying Li, Zikai Yin and Enhong Chen

16. Multi-behavior Self-supervised Learning for Recommendation

Jingcao Xu, Chaokun Wang, Cheng Wu, Yang Song, Kai Zheng, Xiaowei Wang, Changping Wang, Guorui Zhou and Kun Gai

17. MELT: Mutual Enhancement of Long-Tailed User and Item for Sequential Recommendation

Kibum Kim, Dongmin Hyun, Sukwon Yun and Chanyoung Park

18. Single-shot Feature Selection Framework for Multi-task Deep Recommender Systems

Yejing Wang, Zhaocheng Du, Xiangyu Zhao, Bo Chen, Huifeng Guo, Ruiming Tang and Zhenhua Dong

19. Editable User Profiles for Controllable Text Recommendations

Sheshera Mysore, Mahmood Jasim, Andrew Mccallum and Hamed Zamani

20. Intent-aware Ranking Ensemble for Personalized Recommendation

Jiayu Li, Peijie Sun, Zhefan Wang, Weizhi Ma, Yangkun Li, Min Zhang, Zhoutian Feng and Daiyue Xue

21. RCENR: A Reinforced and Contrastive Heterogeneous Network Reasoning Model for Explainable News Recommendation

Hao Jiang, Chuanzhen Li, Juanjuan Cai and Jingling Wang

22. Candidateaware Graph Contrastive Learning for Recommendation

Wei He, Guohao Sun, Jinhu Lu and Xiu Susie Fang

23. LightGT: A Light Graph Transformer for Multimedia Recommendation

Yinwei Wei, Wenqi Liu, Fan Liu, Xiang Wang, Liqiang Nie and Tat-Seng Chua

24. AdaMCL: Adaptive Fusion Multi-View Contrastive Learning for Collaborative Filtering

Guanghui Zhu, Wang Lu, Chunfeng Yuan and Yihua Huang

25. Mixed-Curvature Manifolds Interaction Learning for Knowledge Graph-aware Recommendation

Jihu Wang, Yuliang Shi, Han Yu, Xinjun Wang, Zhongmin Yan and Fanyu Kong

26. Multimodal Counterfactual Learning Network for Multimedia-based Recommendation

Shuaiyang Li, Dan Guo, Kang Liu, Richang Hong and Feng Xue

27. Beyond Two-Tower Matching: Learning Sparse Retrievable Interaction Models for Recommendation

Liangcai Su, Fan Yan, Jieming Zhu, Xi Xiao, Haoyi Duan, Zhou Zhao, Zhenhua Dong and Ruiming Tang

28. HDNR: A Hyperbolic-Based Debiased Approach for Personalized News Recommendation

Shicheng Wang, Shu Guo, Lihong Wang, Tingwen Liu and Hongbo Xu

29. Adaptive Graph Representation Learning for Next POI Recommendation

Zhaobo Wang, Yanmin Zhu, Chunyang Wang, Wenze Ma, Bo Li and Jiadi Yu

30. Alleviating Matthew Effect of Offline Reinforcement Learning in Recommendation

Chongming Gao, Kexin Huang, Jiawei Chen, Yuan Zhang, Biao Li, Peng Jiang, Shiqi Wang, Zhong Zhang and Xiangnan He

31. Spatio-Temporal Hypergraph Learning for Next POI Recommendation

Xiaodong Yan, Tengwei Song, Yifeng Jiao, Jianshan He, Jiaotuan Wang, Ruopeng Li and Wei Chu

32. Knowledge-refined Denoising Network for Robust Recommendation

Xinjun Zhu, Yuntao Du, Yuren Mao, Lu Chen, Yujia Hu and Yunjun Gao

33. Distillation-Enhanced Graph Masked Autoencoders for Bundle Recommendation

Yuyang Ren, Zhang Haonan, Luoyi Fu, Xinbing Wang and Chenghu Zhou

34. Distributionally Robust Sequential Recommendation

Rui Zhou, Xian Wu, Zhaopeng Qiu, Yefeng Zheng and Xu Chen

35. Reformulating CTR Prediction: Learning Invariant Feature Interactions for Recommendation

Yang Zhang, Tianhao Shi, Fuli Feng, Wenjie Wang, Dingxian Wang, Xiangnan He and Yongdong Zhang

36. Model-agnostic Behavioral Distillation For Cold-start Item Recommendation

Zefan Wang, Hao Chen, Xiao Huang, Yufeng Qian, Zhetao Li and Feiran Huang

37. Measuring Item Global Residual Value for Fair Recommendation

Jiayin Wang, Weizhi Ma, Chumeng Jiang, Min Zhang, Yuan Zhang, Biao Li and Peng Jiang

38. Curse of Low Dimensionality in Recommender Systems

Naoto Ohsaka and Riku Togashi

39. Its Enough: Relaxing Diagonal Constraints in Regression-based Linear Recommender Models

Jaewan Moon, Hye Young Kim and Jongwuk Lee

40. Beyond the Overlapping Users: Cross-Domain Recommendation via Adaptive Anchor Link Learning

Yi Zhao, Chaozhuo Li, Jiquan Peng, Xiaohan Fang, Feiran Huang, Senzhang Wang, Xing Xie and Jibing Gong

41. LOAM: Improving Long-tail Session-based Recommendation via Niche Walk Augmentation and Tail Session Mixup

Heeyoon Yang, Gahyung Kim, Jee-Hyong Lee and YunSeok Choi

42. Diffusion Recommender Model

Wenjie Wang, Yiyan Xu, Fuli Feng, Xinyu Lin, Xiangnan He and Tat-Seng Chua

43. Causal Decision Transformer for Recommender Systems via Offline Reinforcement Learning

Siyu Wang, Xiaocong Chen, Lina Yao and Dietmar Jannach

44. Hydrus: Improving Quality of Experience in Recommendation Systems by Making Latency-Accuracy Tradeoffs

Zhiyu Yuan, Kai Ren, Gang Wang and Xin Miao

45. Manipulating Federated Recommender Systems: Poisoning with Synthetic Users and Its Countermeasures

Wei Yuan, Quoc Viet Hung Nguyen, Tieke He, Liang Chen and Hongzhi Yin

46. Contrastive State Augmentations for Reinforcement Learning-Based Recommender Systems

Zhaochun Ren, Na Huang, Yidan Wang, Pengjie Ren, Jun Ma, Jiahuan Lei, Xinlei Shi, Hengliang Luo, Joemon Jose and Xin Xin

47. Multi-view Hypergraph Contrastive Policy Learning for Conversational Recommendation

Sen Zhao, Wei Wei, Xian-Ling Mao, Shuai Zhu, Minghui Yang, Zujie Wen, Dangyang Chen and Feida Zhu

48. Rectifying Unfairness in Recommendation Feedback Loop

Mengyue Yang, Jun Wang and Jean-Francois Ton

49. Next Basket Recommendation with Intent-aware Hypergraph Adversarial Network

Ran Li, Liang Zhang, Guannan Liu and Junjie Wu

50. Masked Graph Transformer for Recommendation

Chaoliu Li, Chao Huang, Lianghao Xia, Xubin Ren, Yaowen Ye and Yong Xu

51. Improving Implicit Feedback-Based Recommendation through Multi-Behavior Alignment

Xin Xin, Xiangyuan Liu, Hanbing Wang, Pengjie Ren, Zhumin Chen, Jiahuan Lei, Xinlei Shi, Hengliang Luo, Joemon Jose, Maarten de Rijke and Zhaochun Ren

52. PLATE: A Prompt-enhanced Paradigm for Multi-Target Cross-Domain Recommendation

Yuhao Wang, Xiangyu Zhao, Bo Chen, Qidong Liu, Huifeng Guo, Huanshuo Liu, Yichao Wang, Rui Zhang and Ruiming Tang

53. Disentangled Contrastive Collaborative Filtering

Xubin Ren, Chao Huang, Lianghao Xia, Jiashu Zhao and Dawei Yin

54. Ensemble Modeling with Contrastive Knowledge Distillation for Sequential Recommendation

Hanwen Du, Huanhuan Yuan, Pengpeng Zhao, Fuzhen Zhuang, Guanfeng Liu, Lei Zhao, Yanchi Liu and Victor S Sheng

55. Model-Agnostic Decentralized Collaborative Learning for On-Device POI Recommendation

Jing Long, Tong Chen, Quoc Viet Hung Nguyen, Guandong Xu, Kai Zheng and Hongzhi Yin

56. M2EU: Meta Learning for Cold-start Recommendation via Enhancing User Preference Estimation

Zhenchao Wu and Xiao Zhou

57. Dynamic Graph Evolution Learning for Recommendation

Haoran Tang, Shiqing Wu, Guandong Xu and Qing Li

58. Linear Attention Mechanism for Long-term Sequential Recommender Systems

Langming Liu, Xiangyu Zhao, Chi Zhang, Jingtong Gao, Wanyu Wang, Wenqi Fan, Yiqi Wang, Ming He, Zitao Liu and Qing Li

59. Mining Stable Preferences: Adaptive Modality Decorrelation for Multimedia Recommendation

Jinghao Zhang, Qiang Liu, Shu Wu and Liang Wang

60. Graph Masked Autoencoder for Sequential Recommendation

Yaowen Ye, Chao Huang and Lianghao Xia

61. Wisdom of Crowds and Fine-Grained Learning for Serendipity Recommendations

Zhe Fu, Xi Niu and Li Yu

62. When Search Meets Recommendation: Learning Disentangled Search Representation for Recommendation

Zihua Si, Zhongxiang Sun, Xiao Zhang, Jun Xu, Xiaoxue Zang, Yang Song, Kun Gai and Ji-Rong Wen

63. Adaptive Popularity Debiasing Aggregator for Graph Collaborative Filtering

Huachi Zhou, Hao Chen, Junnan Dong, Daochen Zha, Chuang Zhou and Xiao Huang

64. Meta-optimized Contrastive Learning for Sequential Recommendation

Xiuyuan Qin, Huanhuan Yuan, Pengpeng Zhao, Junhua Fang, Fuzhen Zhuang, Guanfeng Liu, Yanchi Liu and Victor Sheng

65. Triple Structural Information Modelling for Accurate, Explainable and Interactive Recommendation

Jiahao Liu, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Li Shang and Ning Gu

66. Blurring-Sharpening Process Models for Collaborative Filtering

Jeongwhan Choi, Seoyoung Hong, Noseong Park and Sung-Bae Cho

67. When Newer is Not Better: Does Deep Learning Really Benefit Recommendation From Implicit Feedback

Yushun Dong, Jundong Li and Tobias Schnabel

68. Dual Contrastive Transformer for Hierarchical Preference Modeling in Sequential Recommendation

Chengkai Huang, Shoujin Wang, Xianzhi Wang and Lina Yao

69. Learning Fine-grained User Interests for Micro-video Recommendation

Yu Shang, Chen Gao, Jiansheng Chen, Depeng Jin, Yong Li and Meng Wang

70. A Generic Learning Framework for Sequential Recommendation with Distribution Shifts

Zhengyi Yang, Xiangnan He, Jizhi Zhang, Jiancan Wu, Xin Xin, Jiawei Chen and Xiang Wang

71. Frequency Enhanced Hybrid Attention Network for Sequential Recommendation

Xinyu Du, Huanhuan Yuan, Pengpeng Zhao, Jianfeng Qu, Fuzhen Zhuang, Guanfeng Liu, Yanchi Liu and Victor S Sheng

72. Fine-Grained Preference-Aware Personalized Federated POI Recommendation with Data Sparsity

Xiao Zhang, Ziming Ye, Jianfeng Lu, Fuzhen Zhuang, Yanwei Zheng and Dongxiao Yu

73. News Popularity Beyond the Click-Through-Rate for Personalized Recommendations

Ashutosh Nayak, Mayur Garg and Rajasekhara Reddy Duvvuru Muni

在所接收的短文列表中推荐系统相关话题主要包括：会话推荐、点击率预估、因果推荐系统、图对比推荐系统、基于评论的推荐系统、序列推荐、冷启动推荐等。

https://sigir.org/sigir2023/program/accepted-papers/short-papers/

具体的短文推荐系统相关标题整理如下：

1. Mining Interest Trends and Adaptively Assigning Sample Weight for Session-based Recommendation

Kai Ouyang, Xianghong Xu, Miaoxin Chen, Zuotong Xie, Hai-Tao Zheng, Shuangyong Song and Yu Zhao

2. CEC: Towards Learning Global Optimized Recommendation through Causality Enhanced Conversion Model

Ran Le, Guoqing Jiang, Xiufeng Shu, Ruidong Han, Qianzhong Li, Yacheng Li, Xiang Li and Wei Lin

3. Computational Versus Perceived Popularity Miscalibration in Recommender Systems

Oleg Lesota, Gustavo Escobedo, Yashar Deldjoo, Bruce Ferwerda, Simone Kopeinik, Elisabeth Lex, Navid Rekabsaz and Markus Schedl

4. Always Strengthen Your Strengths: A Drift-Aware Incremental Learning Framework for CTR Prediction

Congcong Liu, Fei Teng, Xiwei Zhao, Zhangang Lin, Jinghe Hu and Jingping Shao

5. Quantifying and Leveraging User Fatigue for Interventions in Recommender Systems

Hitesh Sagtani, Madan Gopal Jhawar, Akshat Gupta and Rishabh Mehrotra

6. ADL: Adaptive Distribution Learning Framework for Multi-Scenario CTR Prediction

Jinyun Li, Huiwen Zheng, Yuanlin Liu, Minfang Lu, Lixia Wu and Haoyuan Hu

7. A Model-Agnostic Popularity Debias Training Framework for Click-Through Rate Prediction in Recommender System

Fan Zhang and Qijie Shen

8. Graph Collaborative Signals Denoising and Augmentation for Recommendation

Ziwei Fan, Ke Xu, Zhang Dong, Hao Peng, Jiawei Zhang and Philip S Yu

9. Denoise to protect: a method to robustify visual recommenders from adversaries

Felice Antonio Merra, Vito Walter Anelli, Tommaso Di Noia, Daniele Malitesta and Alberto Carlo Maria Mancino

10. Model-free Reinforcement Learning with Stochastic Reward Stabilization for Recommender Systems

Tianchi Cai, Shenliao Bao, Jiyan Jiang, Shiji Zhou, Wenpeng Zhang, Lihong Gu, Jinjie Gu and Guannan Zhang

11. Context-Aware Modeling via Simulated Exposure Page for CTR Prediction in Meituan Waimai

Xiang Li, Shuwei Chen, Jian Dong, Jin Zhang, Yongkang Wang, Xingxing Wang and Dong Wang

12. Review-based Multi-intention Contrastive Learning for Recommendation

Wei Yang, Tengfei Huo, Zhiqiang Liu and Chi Lu

13. Simplifying Content-Based Neural News Recommendation: On User Modeling and Training Objectives

Andreea Iana, Goran Glava and Heiko Paulheim

14. Personalized Dynamic Recommender System for Investors

Takehiro Takayanagi, Chung-Chi Chen and Kiyoshi Izumi

15. WSFE: Wasserstein Sub-graph Feature Encoder for Effective User Segmentation in Collaborative Filtering

Yankai Chen, Yifei Zhang, Menglin Yang, Zixing Song, Chen Ma and Irwin King

16. Hard Negative Mining with Neighborhood Similarity for Sequential Recommendation

Lu Fan, Jiashu Pu, Rongsheng Zhang and Xiao-Ming Wu

17. Personalized Showcases: Generating Multi-Modal Explanations for Recommendations

An Yan, Zhankui He, Jiacheng Li, Tianyang Zhang and Julian McAuley

18. Improving News Recommendation via Bottlenecked Multi-task Pre-training

Xiongfeng Xiao, Qing Li, Songlin Liu and Kun Zhou

19. Attention Mixtures for Time-Aware Sequential Recommendation

Viet Anh Tran, Guillaume Salha-Galvan, Bruno Sguerra and Romain Hennequin

20. Sharpness-Aware Graph Collaborative Filtering

Huiyuan Chen, Chin-Chia Michael Yeh, Yujie Fan, Yan Zheng, Junpeng Wang, Vivian Lai, Mahashweta Das and Hao Yang

21. Connecting Unseen Domains: Cross-Domain Invariant Learning in Recommendation

Yang Zhang, Yue Shen, Dong Wang, Jinjie Gu and Guannan Zhang

22. Unbiased Pairwise Learning from Implicit Feedback for Recommender Systems without Biased Variance Control

Yi Ren, Hongyan Tang, Jiangpeng Rong and Siwen Zhu

23. Uncertainty-aware Consistency Learning for Cold-Start Item Recommendation

Taichi Liu, Chen Gao, Zhenyu Wang, Dong Li, Jianye Hao, Depeng Jin and Yong Li

24. Rows or Columns Minimizing Presentation Bias When Comparing Multiple Recommender Systems

Patrik Dokoupil, Ladislav Peska and Ludovico Boratto

25. uCTRL: Unbiased Contrastive Representation Learning via Alignment and Uniformity for Collaborative Filtering

Jae-woong Lee, Seongmin Park, Mincheol Yoon and Jongwuk Lee

26. Forget Me Now: Fast and Exact Unlearning in Neighborhood-based Recommendation

Sebastian Schelter, Mozhdeh Ariannezhad and Maarten de Rijke

27. Robust Causal Inference for Recommender System to Overcome Noisy Confounders

Zhiheng Zhang, Quanyu Dai, Xu Chen, Zhenhua Dong and Ruiming Tang

28. LogicRec: Recommendation with Users Logical Requirements

Zhenwei Tang, Griffin Floto, Armin Toroghi, Shichao Pei, Xiangliang Zhang and Scott Sanner

29. Attention-guided Multi-step Fusion: A Hierarchical Fusion Network for Multimodal Recommendation

Yan Zhou, Jie Guo, Hao Sun, Bin Song and Fei Richard Yu

30. User-Dependent Learning to Debias for Recommendation

Fangyuan Luo and Jun Wu

31. TAML: Time-Aware Meta Learning for Cold-Start Problem in News Recommendation

Jingyuan Li, Yue Zhang, Xuan Lin, Xinxing Yang, Ge Zhou, Longfei Li, Hong Chen and Jun Zhou

32. The Dark Side of Explanations: Poisoning Recommender Systems with Counterfactual Examples

Ziheng Chen, Jia Wang, Gabriele Tolomei, Fabrizio Silvestri and Yongfeng Zhang

33. Prediction then Correction: An Abductive Prediction Correction Method for Sequential Recommendation

Yang Zhang, Yulong Huang, Qifan Wang, Chenxu Wang and Fuli Feng

34. Attacking Pre-trained Recommendation

Yiqing Wu, Ruobing Xie, Zhao Zhang, Yongchun Zhu, Fuzhen Zhuang, Jie Zhou, Yongjun Xu and Qing He

35. FINAL:Factorized Interaction Layer for CTR Prediction

Jieming Zhu, Qinglin Jia, Guohao Cai, Quanyu Dai, Jingjie Li, Zhenhua Dong, Ruiming Tang and Rui Zhang

36. Inference at Scale: Significance Testing for Large Search and Recommendation Experiments

Ngozi Ihemelandu and Michael D Ekstrand

37. Causal Disentangled Variational Auto-Encoder for Preference Understanding in Recommendation

Siyu Wang, Xiaocong Chen, Quan Z Sheng, Yihong Zhang and Lina Yao

38. Allocate According to Potential: Towards a Win-Win Recommendation for Popularity Debias and Performance Boost

Yuanhao Liu, Qi Cao, Huawei Shen, Yunfan Wu, Shuchang Tao and Xueqi Cheng

39. Uncertainty-based Heterogeneous Privileged Knowledge Distillation for Recommendation System

Ang Li, Jian Hu, Ke Ding, Xiaolu Zhang, Jun Zhou, Yong He and Xu Min

40. Optimizing Reciprocal Rank with Bayesian Average for improved Next Item Recommendation

Xiangkui Lu, Jun Wu and Jianbo Yuan

NIPS 2023

1. Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach

2. An Empirical Study Towards Prompt-Tuning for Graph Contrastive Pre-Training in Recommendations

3. Recommender Systems with Generative Retrieval

4. Theoretically Guaranteed Bidirectional Data Rectification for Robust Sequential Recommendation

5. Estimating Propensity for Causality-based Recommendation without Exposure Data

6. REFINE: A Fine-Grained Medication Recommendation System Using Deep Learning and Personalized Drug Interaction Modeling

7. Generate What You Prefer: Reshaping Sequential Recommendation via Guided Diffusion

8. Lending Interaction Wings to Recommender Systems with Conversational Agents

9. KuaiSim: A Comprehensive Simulator for Recommender Systems

10. On the Relationship Between Relevance and Conflict in Online Social Link Recommendations

11. Multi-Objective Intrinsic Reward Learning for Conversational Recommender Systems

12. Supply-Side Equilibria in Recommender Systems

13. UltraRE: Enhancing RecEraser for Recommendation Unlearning via Error Decomposition

14. Cascading Bandits: Optimizing Recommendation Frequency in Delayed

15. Rethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial?

16. REASONER: An Explainable Recommendation Dataset with Comprehensive Labeling Ground Truths

17. Wyze Rule: Federated Rule Dataset for Rule Recommendation Benchmarking

18. Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation

19. Enhancing User Intent Capture in Session-Based Recommendation with Attribute Patterns

20. Fairly Recommending with Social Attributes: A Flexible and Controllable Optimization Approach

CIKM 2023?

SPM: Structured Pretraining and Matching Architectures for Relevance Modeling in Meituan Search?
#相关性匹配 #预训练 #美团?
#https://arxiv.org/pdf/2308.07711.pdf
FiBiNet++: Reducing Model Size by Low Rank Feature Interaction Layer for CTR Prediction?
#特征交叉 #CTR预估 #新浪?
#https://arxiv.org/pdf/2209.05016.pdf
Adaptive Multi-Modalities Fusion in Sequential Recommendation Systems?
#序列推荐 #图神经网络 # 多模态?
#https://arxiv.org/pdf/2308.15980.pdf
RecRec: Algorithmic Recourse for Recommender System?
#可解释性推荐 #Pinterest?
#https://arxiv.org/pdf/2308.14916.pdf
Text Matching Improves Sequential Recommendation by Reducing Popularity Biases?
#序列推荐 #消偏?
#https://arxiv.org/pdf/2308.14029.pdf
Learning and Optimization of Implicit Negative Feedback for Industrial Short-video Recommender System?
#负反馈 #短视频推荐 #快手?
#https://arxiv.org/pdf/2308.13249.pdf
KuaiSAR: A Unified Search And Recommendation Dataset?
#数据集 #快手?
#https://arxiv.org/pdf/2306.07705.pdf
Meta-Learning with Adaptive Weighted Loss for Imbalanced Cold-Start Recommendation?
#元学习 #冷启动推荐?
#https://arxiv.org/pdf/2302.14640.pdf
AdaMCT: Adaptive Mixture of CNN-Transformer for Sequential Recommendation?
#序列推荐 #Transformer?
#https://arxiv.org/pdf/2205.08776.pdf
Low-bit Quantization for Deep Graph Neural Networks with Smoothness-aware Message Propagation?
#图神经网络?
#https://arxiv.org/pdf/2308.14949.pdf
Group Identification via Transitional Hypergraph Convolution with Cross-view Self-supervised Learning?
#群体识别 #超图 #自监督学习?
#https://arxiv.org/pdf/2308.08620.pdf
Preference Modeling Based on User Reviews with Item Images and Textual Information via Graph Learning?
#图神经网络 #用户建模 #亚马逊?
#https://arxiv.org/pdf/2308.09943.pdf
Homophily-enhanced Structure Learning for Graph Clustering?
#图聚类 #图结构学习?
#https://arxiv.org/pdf/2308.05309.pdf
Dual Intents Graph Modeling for User-centric Group Discovery?
#群组推荐 #群体识别 #图神经网络?
#https://arxiv.org/pdf/2308.05013.pdf
Leveraging Watch-time Feedback for Short-Video Recommendations: A Causal Labeling Framework?
#消偏 #因果推荐 #短视频推荐 #快手?
#https://arxiv.org/pdf/2306.17426.pdf
All about Sample-Size Calculations for A/B Testing: Novel Extensions & Practical Guide?
#A/B测试 #线上评估 #苹果?
#https://arxiv.org/pdf/2305.16459.pdf
Counterfactual Graph Augmentation for Consumer Unfairness Mitigation in Recommender Systems?
#推荐公平性 #可解释性?
#https://arxiv.org/pdf/2308.12083.pdf
How Expressive are Graph Neural Networks in Recommendation??
#图神经网络 #推荐?
#https://arxiv.org/pdf/2308.11127.pdf
Single-User Injection for Invisible Shilling Attack against Recommender Systems?
#推荐攻击 #对抗攻击?
#https://arxiv.org/pdf/2308.10467.pdf
Large Language Models as Zero-Shot Conversational Recommenders?
#对话推荐 #语言模型 #公开数据集?
#https://arxiv.org/pdf/2308.10053.pdf
MUSE: Music Recommender System with Shuffle Play Recommendation Enhancement?
#会话推荐 #自监督学习 #音乐推荐?
#https://arxiv.org/pdf/2308.09649.pdf
SHARK: A Lightweight Model Compression Approach for Large-scale Recommender Systems?
#模型压缩 #特征选择 #快手?
#https://arxiv.org/pdf/2308.09395.pdf
AutoSeqRec: Autoencoder for Efficient Sequential Recommendation?
#序列推荐 #自编码?
#https://arxiv.org/pdf/2308.06878.pdf
Toward a Better Understanding of Loss Functions for Collaborative Filtering?
#协同过滤 #损失函数 #alignment and uniformity?
#https://arxiv.org/pdf/2308.06091.pdf
Deep Context Interest Network for Click-Through Rate Prediction?
#CTR预估 #用户行为建模 #美团?
#https://arxiv.org/pdf/2308.06037.pdf
Deep Task-specific Bottom Representation Network for Multi-Task Recommendation?
#多任务学习 #行为建模 #阿里?
#https://arxiv.org/pdf/2308.05996.pdf
Multi-domain Recommendation with Embedding Disentangling and Domain Alignment?
#多域推荐 #信息解耦?
#https://arxiv.org/pdf/2308.05508.pdf
Parallel Knowledge Enhancement based Framework for Multi-behavior Recommendation?
#多行为推荐 #多任务学习?
#https://arxiv.org/pdf/2308.04807.pdf
Entire Space Cascade Delayed Feedback Modeling for Effective Conversion Rate Prediction?
#CVR预估 #样本选择 #阿里?
#https://arxiv.org/pdf/2308.04768.pdf
Scalable Neural Contextual Bandit for Recommender Systems?
#强化学习 #EE问题 #MetaAI?
#https://arxiv.org/pdf/2306.14834.pdf

WSDM 2023

1. Towards Universal Cross-Domain Recommendation
2. IDNP: Interest Dynamics Modeling using Generative Neural Processes for Sequential Recommendation
3. Learning to Distinguish Multi-User Coupling Behaviors for TV Recommendation
4. One for All, All for One: Learning and Transferring User Embeddings for Cross-Domain Recommendation
5. Slate-Aware Ranking for Recommendation
6. Knowledge Enhancement for Contrastive Multi-Behavior Recommendation
7. Disentangled Representation for Diversified Recommendations
8. Cognition-aware Knowledge Graph Reasoning for Explainable Recommendation
9. Self-Supervised Group Graph Collaborative Filtering for Group Recommendation
10. Calibrated Recommendations as a Maximum Flow Problem
11. DisenPOI: Disentangling Sequential and Geographical Influence for Point-of-Interest Recommendation
12. Multi-Intentions Oriented Contrastive Learning for Sequential Recommendation
13. Generative Slate Recommendation with Reinforcement Learning
14. MUSENET: Multi-Scenario Learning for Repeat-Aware Personalized Recommendation
15. A Personalized Neighborhood-based Model for Within-basket Recommendation in Grocery Shopping
16. SGCCL: Siamese Graph Contrastive Consensus Learning for Personalized Recommendation
17. Relation Preference oriented High-order Sampling for Recommendation
18. Variational Reasoning over Incomplete Knowledge Graphs for Conversational Recommendation
19. Exploiting Explicit and Implicit Item relationships for Session-based Recommendation
20. Range Restricted Route Recommendation Based on Spatial Keyword
21. Meta Policy Learning for Cold-Start Conversational Recommendation
22. Efficiently Leveraging Multi-level User Intent for Session-based Recommendation via Atten-Mixer Network
23. Improving News Recommendation with Channel-Wise Dynamic Representations and Contrastive User Modeling
24. Simplifying Graph-based Collaborative Filtering for Recommendation
25. AutoGen: An Automated Dynamic Model Generation Framework for Recommender System
26. A Causal View for Item-level Effect of Recommendation on User Preference
27. Federated Unlearning for On-Device Recommendation
28. Explicit Counterfactual Data Augmentation for Recommendation
29. Uncertainty Quantification for Fairness in Two-Stage Recommender Systems
30. DGRec: Graph Neural Network for Recommendation with Diversified Embedding Generation
31. Unbiased Knowledge Distillation for Recommendation
32. VRKG4Rec: Virtual Relational Knowledge Graph for Recommendation
33. Knowledge-Adaptive Contrastive Learning for Recommendation
34. Heterogeneous Graph Contrastive Learning for Recommendation
35. Disentangled Negative Sampling for Collaborative Filtering
36. Separating Examination and Trust Bias from Click Predictions for Unbiased Relevance Ranking
37. A Bird’s-eye View of Reranking: from List Level to Page Level
38. CL4CTR: A Contrastive Learning Framework for CTR Prediction
39. Directed Acyclic Graph Factorization Machines for CTR Prediction via Knowledge Distillation
40. Pairwise Fairness in Ranking as a Dissatisfaction Measure
41. Marginal-Certainty-aware Fair Ranking Algorithm
42. An F-shape Click Model for Information Retrieval on Multi-block Mobile Pages

AAAI?2023

1.?Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion

n Code：https://github.com/amazon-research/

n Area：Others

2.?POEM: Polarization of Embeddings for Domain-Invariant Representations

n Code：None

n Area：领域泛化(DG)

3.?EMEF: Ensemble Multi-Exposure Image Fusion

n Code：https://github.com/medalwill/EMEF

n Area：多曝光图像融合 (MEF)?

4.?AdversarialWord Dilution as Text Data Augmentation in Low-Resource Regime

n Code：None

n Area：数据增强

5.?"Nothing Abnormal": Disambiguating Medical Reports via Contrastive Knowledge Infusion

n Code：https://github.com/ZexueHe/Med-DEPEN

n Area：医学报告语义消歧

6.?Instance Smoothed Contrastive Learning for Unsupervised Sentence Embedding

n Code：https://github.com/dll-wu/IS-CSE

n Area：无监督句子嵌入

7.?FastAMI -- a Monte Carlo Approach to the Adjustment for Chance in Clustering Comparison Metrics

n Code：https://github.com/mad-lab-fau/fastami-benchmark

n Area：聚类

8.?A Parameterized Theory of PAC Learning

n Code：None

n Area：PAC学习

9.?Multi-Modality Deep Network for Extreme Learned Image Compression

n Code：None

n Area：图像压缩

10.?ESPT: A Self-Supervised Episodic Spatial Pretext Task for Improving Few-Shot Learning

n Code：https://github.com/Whut-YiRong/ESPT

n Area：小样本图像分类

11.?Pointerformer: Deep Reinforced Multi-Pointer Transformer for the Traveling Salesman Problem

n Code：None

n Area：旅行商问题（Traveling Salesman Problem，TSP）

12.?H-TSP: Hierarchically Solving the Large-Scale Travelling Salesman Problem

n Code：None

n Area：旅行商问题（Traveling Salesman Problem，TSP）

13.?Forecasting with Sparse but Informative Variables: A Case Study in Predicting Blood Glucose

n Code：None

n Area：时间序列预测

14.?Meta-Auxiliary Learning for Adaptive Human Pose Prediction

n Code：None

n Area：人体姿态预测

15.?Data-Efficient Image Quality Assessment with Attention-Panel Decoder

n Code：https://github.com/narthchin/DEIQT

n Area：图像质量评估

16.?Neural Diffeomorphic Non-uniform B-spline Flows

n Code：https://github.com/smhongok/Non-uniform-B-spline-Flow

n Area：Others

17.?Grouped Knowledge Distillation for Deep Face Recognition

n Code：None

n Area：人脸识别

18.?Nearest-Neighbor Sampling Based Conditional Independence Testing

n Code：None

n Area：Others

19.?Continual Graph Convolutional Network for Text Classification

n Code：https://github.com/Jyonn/ContGCN

n Area：图卷积网络应用于文本分类

20.?Can Adversarial Networks Make Uninformative Colonoscopy Video Frames Clinically Informative?

n Code：None

n Area：对抗网络

21.?Locate Then Generate: Bridging Vision and Language with Bounding Box for Scene-Text VQA

n Code：None

n Area：多模态文本视觉问答

22.?FinalMLP: An Enhanced Two-Stream MLP Model for CTR Prediction

n Code：https://xpai.github.io/FinalMLP

n Area：推荐系统CTR预测

23.?Rethinking interpretation: Input-agnostic saliency mapping of deep visual classifiers

n Code：None

n Area：Others

24.?Scalable Bayesian Meta-Learning through Generalized Implicit Gradients

n Code：None

n Area：元学习

25.?Boosting Few-Shot Text Classification via Distribution Estimation

n Code：None

n Area：少样本文本分类

26.?Learning Second-Order Attentive Context for Efficient Correspondence Pruning

n Code：None

n Area：对应修剪

27.?GANTEE: Generative Adversatial Network for Taxonomy Entering Evaluation

n Code：None

n Area：生成对抗网络

28.?Learning Fractals by Gradient Descent

n Code：https://github.com/andytu28/LearningFractals

n Area：分形

29.?Heterogeneous-Branch Collaborative Learning for Dialogue Generation

n Code：None

n Area：对话生成

30.?Bidirectional Domain Mixup for Domain Adaptive Semantic Segmentation

n Code：https://sites.google.com/view/bidirectional-domain-mixup

n Area：域自适应语义分割

31.?On the Calibration and Uncertainty with Pólya-Gamma Augmentation for Dialog Retrieval Models

n Code：None

n Area：对话检索

32.?CoordFill: Efficient High-Resolution Image Inpainting via Parameterized Coordinate Querying

n Code：https://github.com/NiFangBaAGe/CoordFill

n Area：图像修复

33.?Fast Regularized Discrete Optimal Transport with Group-Sparse Regularizers

n Code：None

n Area：正则化离散最优传输

34.?Deep Spiking Neural Networks with High Representation Similarity Model Visual Pathways of Macaque and Mouse

n Code：https://github.com/Grasshlw/SNN-Neural-Similarity

n Area：Others

35.?Conceptual Reinforcement Learning for Language-Conditioned Tasks

n Code：None

n Area：深度强化学习

36.?Optimal Sparse Recovery with Decision Stumps

n Code：None

n Area：决策树

37.?Finite Based Contraction and Expansion via Models

n Code：None

n Area：Others

38.?Adaptive Texture Filtering for Single-Domain Generalized Segmentation

n Code：None

n Area：语义分割域泛化

39.?Properties of Position Matrices and Their Elections

n Code：None

n Area：Others

40.?Few-Shot Defect Image Generation via Defect-Aware Feature Manipulation

n Code：https://github.com/Ldhlwh/DFMGAN

n Area：少样本缺陷图像生成

41.?Self-Asymmetric Invertible Network for Compression-Aware Image Rescaling

n Code：https://github.com/yang-jin-hai/SAIN

n Area：图像缩放

42.?Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders

n Code：None

n Area：时间序列因果分析

43.?Generalized Semantic Segmentation by Self-Supervised Source Domain Projection and Multi-Level Contrastive Learning

n Code：None

n Area：语义分割域泛化

44.?ParaFormer: Parallel Attention Transformer for Efficient Feature Matching

n Code：None

n Area：特征匹配

45.?Exploiting Multiple Abstractions in Episodic RL via Reward Shaping

n Code：None

n Area：强化学习

46.?Controlling Class Layout for Deep Ordinal Classification via Constrained Proxies Learning

n Code：https://github.com/tenvence/cpl

n Area：深度序数分类

47.?Dish-TS: A General Paradigm for Alleviating Distribution Shift in Time Series Forecasting

n Code：https://github.com/weifantt/Dish-TS

n Area：时间序列预测

48.?City-scale Pollution Aware Traffic Routing by Sampling Max Flows using MCMC

n Code：None

n Area：Others

49.?Self-Supervised Interest Transfer Network via Prototypical Contrastive Learning for Recommendation

n Code：https://github.com/fanqieCoffee/SITN-Supplement

n Area：跨域推荐

50.?Robust Representation Learning by Clustering with Bisimulation Metrics for Visual Reinforcement Learning with Distractions

n Code：https://github.com/MIRALab-USTC/RL-CBM

n Area：强化学习

51.?FTM: A Frame-level Timeline Modeling Method for Temporal Graph Representation Learning

n Code：https://github.com/yeeeqichen/FTM

n Area：时间图表示学习

52.?FiTs: Fine-grained Two-stage Training for Knowledge-aware Question Answering

n Code：https://github.com/yeeeqichen/FiTs

n Area：知识感知问答

53.?GLUECons: A Generic Benchmark for Learning Under Constraints

n Code：None

n Area：集成学习

54.?Pseudo Label-Guided Model Inversion Attack via Conditional Generative Adversarial Network

n Code：https://github.com/LetheSec/PLG-MI-Attack

n Area：模型反转 (MI) 攻击

55.?CMVAE: Causal Meta VAE for Unsupervised Meta-Learning

n Code：https://github.com/GuodongQi/CMVAE

n Area：无监督元学习

56.?Rethinking Data-Free Quantization as a Zero-Sum Game

n Code：https://github.com/hfutqian/AdaSG

n Area：无数据量化 (DFQ)

57.?Delving into the Adversarial Robustness of Federated Learning

n Code：None

n Area：联邦学习

58.?Self-supervised Action Representation Learning from Partial Spatio-Temporal Skeleton Sequences

n Code：https://github.com/YujieOuO/PSTL.git

n Area：骨架动作识别

59.?Multimodal Propaganda Processing

n Code：None

n Area：多模态

60.?Find Beauty in the Rare: Contrastive Composition Feature Clustering for Nontrivial Cropping Box Regression

n Code：None

n Area：自动图像裁剪

61.?Dialogue State Distillation Network with Inter-slot Contrastive Learning for Dialogue State Tracking

n Code：None

n Area：对话状态跟踪（DST）

62.?Improving Interpretability of Deep Sequential Knowledge Tracing Models with Question-centric Cognitive Representations

n Code：https://pykt.org/

n Area：知识追踪 (KT)

63.?Actional Atomic-Concept Learning for Demystifying Vision-Language Navigation

n Code：None

n Area：视觉语言导航 (VLN)

64.?RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQL

n Code：https://github.com/RUCKBReasoning/RESDSQL

n Area：预训练语言模型

65.?Learning by Applying: A General Framework for Mathematical Reasoning via Enhancing Explicit Knowledge Learning

n Code：None

n Area：Others

66.?RAFaRe: Learning Robust and Accurate Non-parametric 3D Face Reconstruction from Pseudo 2D&3D Pairs

n Code：http://github.com/zhuhao-nju/rafare

n Area：3D人脸重建

67.?BEST: BERT Pre-Training for Sign Language Recognition with Coupling Tokenization

n Code：None

n Area：预训练语言模型

68.?Symbolic Metamodels for Interpreting Black-boxes Using Primitive Functions

n Code：None

n Area：机器学习可解释性

69.?Measuring the Privacy Leakage via Graph Reconstruction Attacks on Simplicial Neural Networks

n Code：None

n Area：图重建攻击（GRA）

70.?A Vector Quantized Approach for Text to Speech Synthesis on Real-World Spontaneous Speech

n Code：https://github.com/b04901014/MQTTS

n Area：语音合成

71.?Hierarchical Event Grounding

n Code：https://github.com/JefferyO/Hierarchical-Event-Grounding

n Area：Others

72.?WAT: Improve the Worst-class Robustness in Adversarial Training

n Code：None

n Area：对抗鲁棒性

73.?On Generalized Degree Fairness in Graph Neural Networks

n Code：None

n Area：图神经网络

74.?ShiftDDPMs: Exploring Conditional Diffusion Models by Shifting Diffusion Trajectories

n Code：None

n Area：Diffusion Models

75.?Efficient End-to-End Video Question Answering with Pyramidal Multimodal Transformer

n Code：https://github.com/Trunpm/PMT-AAAI23

n Area：视频问答

76.?Reducing ANN-SNN Conversion Error through Residual Membrane Potential

n Code：https://github.com/hzc1208/ANN2SNN

n Area：尖峰神经网络（SNNs）

77.?Entity-Agnostic Representation Learning for Parameter-Efficient Knowledge Graph Embedding

n Code：None

n Area：表示学习

78.?Continual Learning with Scaled Gradient Projection

n Code：https://github.com/sahagobinda/SGP

n Area：持续学习

79.?IKOL: Inverse kinematics optimization layer for 3D human pose and shape estimation via Gauss-Newton differentiation

n Code：https://github.com/Juzezhang/IKOL

n Area：3D人体姿态估计

80.?Meta Learning in Decentralized Neural Networks: Towards More General AI

n Code：None

n Area：元学习

81.?PAC learning and stabilizing Hedonic Games: towards a unifying approach

n Code：None

n Area：PAC学习

82.?Feature-Space Bayesian Adversarial Learning Improved Malware Detector Robustness

n Code：None

n Area：恶意软件检测

83.?Key Feature Replacement of In-Distribution Samples for Out-of-Distribution Detection

n Code：None

n Area：分布外(OOD)检测

84.?Tagging before Alignment: Integrating Multi-Modal Tags for Video-Text Retrieval

n Code：None

n Area：视频文本检索

85.?AudioEar: Single-View Ear Reconstruction for Personalized Spatial Audio

n Code：https://github.com/seanywang0408/AudioEar

n Area：3D声音渲染

86.?Towards Inference Efficient Deep Ensemble Learning

n Code：https://seqml.github.io/irene

n Area：集成学习

87.?Efficient Enumeration of Markov Equivalent DAGs

n Code：None

n Area：Others

88.?Dynamic Multi-Behavior Sequence Modeling for Next Item Recommendation

n Code：None

n Area：推荐系统

89.?Reachability Analysis of Neural Network Control Systems

n Code：https://github.com/TrustAI/DeepNNC

n Area：神经网络控制器

90.?Qualitative Analysis of a Graph Transformer Approach to Addressing Hate Speech: Adapting to Dynamically Changing Content

n Code：None

n Area：Others

91.?Latent Autoregressive Source Separation

n Code：None

n Area：Others

92.?On the Vulnerability of Backdoor Defenses for Federated Learning

n Code：None

n Area：联邦学习

93.?Foresee What You Will Learn: Data Augmentation for Domain Generalization in Non-stationary Environment

n Code：None

n Area：域泛化

94.?Towards a Holistic Understanding of Mathematical Questions with Contrastive Pre-training

n Code：None

n Area：Others

95.?Graphix-T5: Mixing Pre-Trained Transformers with Graph-Aware Layers for Text-to-SQL Parsing

n Code：None

n Area：文本到 SQL 解析

96.?Towards Voice Reconstruction from EEG during Imagined Speech

n Code：None

n Area：语音合成

97.?Memory-Augmented Theory of Mind Network

n Code：None

n Area：Others

98.?TA-DA: Topic-Aware Domain Adaptation for Scientific Keyphrase Identification and Classification

n Code：None

n Area：关键短语识别和分类

99.?Prompting Neural Machine Translation with Translation Memories

n Code：None

n Area：机器翻译

100.?SHUNIT: Style Harmonization for Unpaired Image-to-Image Translation

n Code：https://github.com/bluejangbaljang/SHUNIT

n Area：图像到图像翻译

101.?Learnable Path in Neural Controlled Differential Equations

n Code：None

n Area：Others

102.?Neighborhood-Regularized Self-Training for Learning with Few Labels

n Code：https://github.com/ritaranx/NeST

n Area：Others

103.?WLD-Reg: A Data-dependent Within-layer Diversity Regularizer

n Code：https://github.com/firasl/AAAI-23-WLD-Reg

n Area：Others

104.?Correlation Loss: Enforcing Correlation between Classification and Localization

n Code：https://github.com/fehmikahraman/CorrLoss

n Area：目标检测

105.?Analogical Inference Enhanced Knowledge Graph Embedding

n Code：None

n Area：知识图嵌入

106.?Task-specific Scene Structure Representations

n Code：https://github.com/jsshin98/

n Area：Others

107.?On the Challenges of using Reinforcement Learning in Precision Drug Dosing: Delay and Prolongedness of Action Effects

n Code：None

n Area：强化学习

108.?Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generation

n Code：https://github.com/GRAPH-0/CDGS

n Area：Diffusion Models

109.?Self-organization Preserved Graph Structure Learning with Principle of Relevant Information

n Code：None

n Area：Others

110.?Resolving Task Confusion in Dynamic Expansion Architectures for Class Incremental Learning

n Code：https://github.com/YellowPancake/TCIL

n Area：增量学习

111.?Model-Based Reinforcement Learning with Multinomial Logistic Function Approximation

n Code：None

n Area：强化学习

112.?Infusing Definiteness into Randomness: Rethinking Composition Styles for Deep Image Matting

n Code：https://github.com/coconuthust/composition

n Area：图像抠图

113.?Truncate-Split-Contrast: A Framework for Learning from Mislabeled Videos

n Code：None

n Area：噪声标签学习

114.?Don't Be So Sure! Boosting ASR Decoding via Confidence Relaxation

n Code：None

n Area：自动语音识别

115.?Ultra-High-Definition Low-Light Image Enhancement: A Benchmark and Transformer-Based Method

n Code：https://github.com/TaoWangzj/LLFormer

n Area：低光图像增强

116.?Generalization Bounds for Inductive Matrix Completion in Low-noise Settings

n Code：None

n Area：Others

117.?RWEN-TTS: Relation-aware Word Encoding Network for Natural Text-to-Speech Synthesis

n Code：None

n Area：文本转语音

118.?Scaling Marginalized Importance Sampling to High-Dimensional State-Spaces via State Abstraction

n Code：None

n Area：强化学习

119.?Interactive Concept Bottleneck Models

n Code：https://github.com/google-research/google_research/tree/master/interactive_cbms

n Area：概念瓶颈模型 (CBM)

120.?Post-hoc Uncertainty Learning using a Dirichlet Meta-Model

n Code：None

n Area：Others

121.?Mitigating Artifacts in Real-World Video Super-Resolution Models

n Code：https://github.com/TencentARC/FastRealVSR

n Area：视频超分辨率

122.?Efficient Exploration in Resource-Restricted Reinforcement Learning

n Code：None

n Area：强化学习

123.?Distantly-Supervised Named Entity Recognition with Adaptive Teacher Learning and Fine-grained Student Ensemble

n Code：https://github.com/zenhjunpro/ATSEN

n Area：NER

124.?Estimating Geographic Spillover Effects of COVID-19 Policies From Large-Scale Mobility Networks

n Code：https://github.com/snap-stanford/covid-spillovers

n Area：Others

125.?HOTCOLD Block: Fooling Thermal Infrared Detectors with a Novel Wearable Design

n Code：https://github.com/weihui1308/HOTCOLDBlock

n Area：对抗攻击

126.?SEPT: Towards Scalable and Efficient Visual Pre-Training

n Code：None

n Area：自监督预训练

127.?Untargeted Attack against Federated Recommendation Systems via Poisonous Item Embeddings and the Defense

n Code：None

n Area：联邦推荐

128.?MAPS-KB: A Million-scale Probabilistic Simile Knowledge Base

n Code：https://github.com/Abbey4799/MAPS-KB

n Area：Others

129.?Networked Restless Bandits with Positive Externalities

n Code：https://github.com/crherlihy/networked_restless_bandits

n Area：Others

130.?VASR: Visual Analogies of Situation Recognition

n Code：https://vasr-dataset.github.io/

n Area：Others

131.?Learning Polysemantic Spoof Trace: A Multi-Modal Disentanglement Network for Face Anti-spoofing

n Code：None

n Area：人脸反欺骗

132.?Fairness and Explainability: Bridging the Gap Towards Fair Model Explanations

n Code：https://github.com/YuyingZhao/FairExplanations-CFA

n Area：机器学习可解释性

133.?Learning Continuous Depth Representation via Geometric Spatial Aggregator

n Code：https://github.com/nana01219/GeoDSR

n Area：深度图超分辨率

134.?Selector-Enhancer: Learning Dynamic Selection of Local and Non-local Attention Operation for Speech Enhancement

n Code：https://github.com/XinmengXu/Selector

n Area：语音增强

135.?FacT: Factor-Tuning for Lightweight Adaptation on Vision Transformer

n Code：https://github.com/JieShibo/PETL-ViT

n Area：ViT

136.?Fast Online Hashing with Multi-Label Projection

n Code：None

n Area：Others

137.?Knowledge-Bridged Causal Interaction Network for Causal Emotion Entailment

n Code：https://github.com/circle-hit/KBCIN

n Area：Others

138.?SSDA3D: Semi-supervised Domain Adaptation for 3D Object Detection from Point Cloud

n Code：https://github.com/yinjunbo/SSDA3D

n Area：点云3D目标检测

139.?Domain-General Crowd Counting in Unseen Scenarios

n Code：https://github.com/ZPDu/Domain-general-Crowd-Counting-in-Unseen-Scenarios

n Area：图像计数

140.?Hierarchical Contrast for Unsupervised Skeleton-based Action Representation Learning

n Code：https://github.com/HuiGuanLab/HiCo

n Area：无监督骨架动作识别

141.?Exploring Stroke-Level Modifications for Scene Text Editing

n Code：https://github.com/qqqyd/MOSTEL

n Area：场景文本编辑 (STE)

142.?Joint Self-Supervised Image-Volume Representation Learning with Intra-Inter Contrastive Clustering

n Code：None

n Area：无监督联邦学习

143.?Improving End-to-end Speech Translation by Leveraging Auxiliary Speech and Text Data

n Code：None

n Area：语音翻译

144.?KPT: Keyword-guided Pre-training for Grounded Dialog Generation

n Code：None

n Area：对话生成

145.?RLogist: Fast Observation Strategy on Whole-slide Images with Deep Reinforcement Learning

n Code：https://github.com/tencent-ailab/RLogist

n Area：全幻灯片图像 (WSI)

146.?Exploring Stochastic Autoregressive Image Modeling for Visual Representation

n Code：https://github.com/qiy20/SAIM

n Area：自回归语言建模 (ALM)

147.?FedALA: Adaptive Local Aggregation for Personalized Federated Learning

n Code：https://github.com/TsingZ0/FedALA

n Area：联邦学习

148.?Improving Simultaneous Machine Translation with Monolingual Data

n Code：https://github.com/hexuandeng/Mono4SiMT

n Area：同步机器翻译 (SiMT)

149.?SumREN: Summarizing Reported Speech about Events in News

n Code：https://github.com/amazon-science/SumREN

n Area：Others

150.?Towards Diverse, Relevant and Coherent Open-Domain Dialogue Generation via Hybrid Latent Variables

n Code：None

n Area：开放域对话生成

151.?MHCCL: Masked Hierarchical Cluster-Wise Contrastive Learning for Multivariate Time Series

n Code：None

n Area：无监督时间序列表示学习

152.?RIPPLE: Concept-Based Interpretation for Raw Time Series Models in Education

n Code：https://github.com/epfl-ml4ed/ripple/

n Area：时间序列

153.?Stable Learning via Sparse Variable Independence

n Code：None

n Area：Others

154.?A Domain-Knowledge-Inspired Music Embedding Space and a Novel Attention Mechanism for Symbolic Music Modeling

n Code：https://github.com/guozixunnicolas/FundamentalMusicEmbedding

n Area：语音信号处理

155.?Integer Subspace Differential Privacy

n Code：None

n Area：Others

156.?When Neural Networks Fail to Generalize? A Model Sensitivity Perspective

n Code：https://github.com/DIAL-RPI/Spectral-Adversarial-Data-Augmentation

n Area：域泛化 (DG)

157.?Neural Representations Reveal Distinct Modes of Class Fitting in Residual Convolutional Networks

n Code：https://github.com/mjamroz90/dnn-class-fitting

n Area：Others

158.?SWL-Adapt: An Unsupervised Domain Adaptation Model with Sample Weight Learning for Cross-User Wearable Human Activity Recognition

n Code：None

n Area：可穿戴人体活动识别

159.?What do you MEME? Generating Explanations for Visual Semantic Role Labelling in Memes

n Code：https://github/com/LCS2-IIITD/LUMEN-Explaining-Memes.

n Area：Others

160.?Purifier: Defending Data Inference Attacks via Transforming Confidence Scores

n Code：None

n Area：Others

161.?Graph Anomaly Detection via Multi-Scale Contrastive Learning Networks with Augmented View

n Code：None

n Area：图异常检测（GAD）

162.?FoPro: Few-Shot Guided Robust Webly-Supervised Prototypical Learning

n Code：https://github.com/yuleiqin/fopro

n Area：网络监督学习 (WSL)

163.?Language Model Pre-training on True Negatives

n Code：None

n Area：预训练语言模型

164.?Learning to Select from Multiple Options

n Code：https://github.com/jiangshdd/LearningToSelect

n Area：文本蕴含

165.?Learning Combinatorial Structures via Markov Random Fields with Sampling through Lovász Local Lemma

n Code：None

n Area：Others

166.?CL3D: Unsupervised Domain Adaptation for Cross-LiDAR 3D Detection

n Code：https://github.com/4DVLab/CL3D.git

n Area：LiDAR 3D检测

167.?Experimental Observations of the Topology of Convolutional Neural Network Activations

n Code：None

n Area：拓扑数据分析

168.?Weakly Supervised 3D Multi-person Pose Estimation for Large-scale Scenes based on Monocular Camera and Single LiDAR

n Code：https://github.com/4DVLab/FusionPose.git

n Area：3D多人姿态估计

169.?Learning Motion-Robust Remote Photoplethysmography through Arbitrary Resolution Videos

n Code：https://github.com/LJW-GIT/Arbitrary_Resolution_rPPG

n Area：Others

170.?NeAF: Learning Neural Angle Fields for Point Normal Estimation

n Code：https://github.com/lisj575/NeAF

n Area：神经角度场（NeAF）

171.?Logic and Commonsense-Guided Temporal Knowledge Graph Completion

n Code：https://github.com/ngl567/LCGE

n Area：时间知识图补全

172.?Linking Sketch Patches by Learning Synonymous Proximity for Graphic Sketch Representation

n Code：https://github.com/CMACH508/SP-gra2seq

n Area：图形草图表示

173.?Toward Robust Diagnosis: A Contour Attention Preserving Adversarial Defense for COVID-19 Detection

n Code：https://github.com/Quinn777/CAP

n Area：Others

174.?Which Shortcut Solution Do Question Answering Models Prefer to Learn?

n Code：None

n Area：QA

175.?Quantization-aware Interval Bound Propagation for Training Certifiably Robust Quantized Neural Networks

n Code：None

n Area：Others

176.?Understanding and Enhancing Robustness of Concept-based Models

n Code：None

n Area：Others

177.?Behavior Estimation from Multi-Source Data for Offline Reinforcement Learning

n Code：None

n Area：强化学习

178.?Similarity Distribution based Membership Inference Attack on Person Re-identification

n Code：None

n Area：行人重识别

179.?An Extreme-Adaptive Time Series Prediction Model Based on Probability-Enhanced LSTM Neural Networks

n Code：None

n Area：时间序列预测

180.?Direct Heterogeneous Causal Learning for Resource Allocation Problems in Marketing

n Code：None

n Area：因果学习

181.?Efficient Mirror Detection via Multi-level Heterogeneous Learning

n Code：https://github.com/Catherine-R-He/

n Area：Others

182.?DQ-DETR: Dual Query Detection Transformer for Phrase Extraction and Grounding

n Code：https://github.com/IDEA-Research/DQ-DETR

n Area：Others

183.?MicroAST: Towards Super-Fast Ultra-Resolution Arbitrary Style Transfer

n Code：https://github.com/EndyWon/MicroAST

n Area：风格迁移

184.?Generalized Category Discovery with Decoupled Prototypical Network

n Code：https://github.com/Lackel/DPN

n Area：广义类别发现

185.?LoNe Sampler: Graph node embeddings by coordinated local neighborhood sampling

n Code：None

n Area：Others

186.?VLTinT: Visual-Linguistic Transformer-in-Transformer for Coherent Video Paragraph Captioning

n Code：https://github.com/UARK-AICV/VLTinT

n Area：视频段落字幕

187.?STAGE: Span Tagging and Greedy Inference Scheme for Aspect Sentiment Triplet Extraction

n Code：None

n Area：情感分析

188.?PUnifiedNER: A Prompting-based Unified NER System for Diverse Datasets

n Code：None

n Area：NER

189.?Alignment-Enriched Tuning for Patch-Level Pre-trained Document Image Models

n Code：https://github.com/MAEHCM/AET

n Area：Others

190.?Differentiable Meta Multigraph Search with Partial Message Propagation on Heterogeneous Information Networks

n Code：None

n Area：异构信息网络

191.?Spatio-Temporal Meta-Graph Learning for Traffic Forecasting

n Code：https://github.com/deepkashiwa20/MegaCRN

n Area：时间序列预测

192.?Maximizing the Probability of Fixation in the Positional Voter Model

n Code：None

n Area：Others

193.?Mixture Manifold Networks: A Computationally Efficient Baseline for Inverse Modeling

n Code：None

n Area：Others

194.?Language-Assisted 3D Feature Learning for Semantic Scene Understanding

n Code：https://github.com/Asterisci/Language-Assisted-3D

n Area：语义场景理解

195.?Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating

n Code：None

n Area：无监督图表示学习

196.?ILSGAN: Independent Layer Synthesis for Unsupervised Foreground-Background Segmentation

n Code：None

n Area：无监督前景-背景分割

197.?Estimating Regression Predictive Distributions with Sample Networks

n Code：https://samplenet.github.io/

n Area：估计深度神经网络预测

198.?GAN Prior based Null-Space Learning for Consistent Super-Resolution

n Code：https://github.com/wyhuai/RND

n Area：超分辨率

199.?Minority-Oriented Vicinity Expansion with Attentive Aggregation for Video Long-Tailed Recognition

n Code：https://github.com/wjun0830/MOVE

n Area：视频长尾识别

200.?NQE: N-ary Query Embedding for Complex Query Answering over Hyper-Relational Knowledge Graphs

n Code：None

n Area：复杂查询回答

WWW 2023

1. Submodular Maximization in the Presence of Biases with Applications to Recommendation

Anay Mehrotra and Nisheeth K. Vishnoi

2. Scoping Fairness Objectives and Identifying Fairness Metrics for Recommender Systems: The Practitioners’ Perspective

Jessie J. Smith, Lex Beattie and Henriette Cramer

3. P-MMF: Provider Max-min Fairness Re-ranking in Recommender System

Chen Xu, Sirui Chen, Jun Xu, Weiran Shen, Xiao Zhang, Gang Wang and Zhenhua Dong

4. Fairly Adaptive Negative Sampling for Recommendations

Xiao Chen, Wenqi Fan, Jingfan Chen, Haochen Liu, Zitao Liu, Qing Li and Zhaoxiang Zhang

5. RL-MPCA: A Reinforcement Learning Based Multi-Phase Computation Allocation Approach for Recommender Systems

Jiahong Zhou, Shunhui Mao, Guoliang Yang, Bo Tang, Qianlong Xie, Lebin Lin, Xingxing Wang and Dong Wang

6. Collaboration-Aware Graph Convolutional Network for Recommender Systems

Yu Wang, Yuying Zhao, Yi Zhang and Tyler Derr

7. Enhancing Hierarchy-Aware Graph Networks with Deep Dual Clustering for Session-based Recommendation

Jiajie Su, Xiaolin Zheng, Weiming Liu, Fei Wu, Chaochao Chen and Haoming Lyu

8. ConsRec: Learning Consensus Behind Interactions for Group Recommendation

Xixi Wu, Yun Xiong, Yao Zhang, Yizhu Jiao, Jiawei Zhang, Yangyong Zhu and Philip Yu

9. Semi-decentralized Federated Ego Graph Learning for Recommendation

Liang Qu, Ningzhi Tang, Ruiqi Zheng, Quoc Viet Hung Nguyen, Zi Huang, Yuhui Shi and Hongzhi Yin

10. Joint Internal Multi-Interest Exploration and External Domain Alignment for Cross Domain Sequential Recommendation

Weiming Liu, Xiaolin Zheng, Chaochao Chen, Jiajie Su, Xinting Liao, Mengling Hu and Yanchao Tan

11. Intra and Inter Domain HyperGraph Convolutional Network for Cross-Domain Recommendation

Zhongxuan Han, Xiaolin Zheng, Chaochao Chen, Wenjie Cheng and Yang Yao

12. Dual Intent Enhanced Graph Neural Network for Session-based New Item Recommendation

Di Jin, Luzhi Wang, Yizhen Zheng, Guojie Song, Fei Jiang, Xiang Li, Wei Lin and Shirui Pan

13. ApeGNN: Node-Wise Adaptive Aggregation in GNNs for Recommendation

Dan Zhang, Yifan Zhu, Yuxiao Dong, Yuandong Wang, Wenzheng Feng, Evgeny Kharlamov and Jie Tang

14. ?Enhancing User Personalization in Conversational Recommenders

Allen Lin, Ziwei Zhu, Jianling Wang and James Caverlee

15. LINet: A Location and Intention-Aware Neural Network for Hotel Group Recommendation

Ruitao Zhu, Detao Lv, Yao Yu, Ruihao Zhu, Zhenzhe Zheng, Ke Bu, Quan Lu and Fan Wu

16. Multi-Modal Adversarial Self-Supervised Learning for Recommendation

Wei Wei, Chao Huang, Lianghao Xia and Chuxu Zhang

17. Distillation from Heterogeneous Models for Top-K Recommendation

Seongku Kang, Wonbin Kweon, Dongha Lee, Jianxun Lian, Xing Xie and Hwanjo Yu

18. ?On the Theories Behind Hard Negative Sampling for Recommendation

Wentao Shi, Jiawei Chen, Fuli Feng, Jizhi Zhang, Junkang Wu, Chongming Gao and Xiangnan He

19. ?Fine-tuning Partition-aware Item Similarities for Efficient and Scalable Recommendation

Tianjun Wei, Jianghong Ma and Tommy W. S. Chow

20. ?Exploration and Regularization of the Latent Action Space in Recommendation

Shuchang Liu, Qingpeng Cai, Bowen Sun, Yuhao Wang, Dong Zheng, Peng Jiang, Kun Gai, Ji Jiang, Xiangyu Zhao and Yongfeng Zhang

21. ? Bootstrap Latent Representations for Multi-modal Recommendation

Xin Zhou, Hongyu Zhou, Yong Liu, Zhiwei Zeng, Chunyan Miao, Pengwei Wang, Yuan You and Feijun Jiang

22. ? Two-Stage Constrained Actor-Critic for Short Video Recommendation

Qingpeng Cai, Zhenghai Xue, Chi Zhang, Wanqi Xue, Shuchang Liu, Ruohan Zhan, Xueliang Wang, Tianyou Zuo, Wentao Xie, Dong Zheng, Peng Jiang and Kun Gai

23. ? Recommendation with Causality enhanced Natural Language Explanations

Jingsen Zhang, Xu Chen, Jiakai Tang, Weiqi Shao, Quanyu Dai, Zhenhua Dong and Rui Zhang

24. ?Cross-domain recommendation via user interest alignment

Chuang Zhao, Hongke Zhao, Ming He, Jian Zhang and Jianping Fan

25. ? A Simple Data-Augmented Framework For Smoothed Recommender System

Zhenlei Wang and Xu Chen

26. ? Dual-interest Factorization-heads Attention for Sequential Recommendation

Guanyu Lin, Chen Gao, Yu Zheng, Jianxin Chang, Yanan Niu, Yang Song, Zhiheng Li, Depeng Jin and Yong Li

27. ? Contrastive Collaborative Filtering for Cold-Start Item Recommendation

Zhihui Zhou, Lilin Zhang and Ning Yang

28. ? Anti-FakeU: Defending Shilling Attacks on Graph Neural Network based Recommender Model

Xiaoyu You, Chi Lee, Daizong Ding, Mi Zhang, Fuli Feng, Xudong Pan and Min Yang

29. ? Compressed Interaction Graph based Framework for Multi-behavior Recommendation

Wei Guo, Chang Meng, Enming Yuan, Zhicheng He, Huifeng Guo, Yingxue Zhang, Bo Chen, Yaochen Hu, Ruiming Tang, Xiu Li and Rui Zhang

30. ? A Counterfactual Collaborative Session-based Recommender System

Wenzhuo Song, Shoujin Wang, Yan Wang, Kunpeng Liu, Xueyan Liu and Minghao Yin

31. ?Correlative Preference Transfer with Hierarchical Hypergraph Network for Multi-Domain Recommendation

Zixuan Xu, Penghui Wei, Shaoguo Liu, Weimin Zhang, Liang Wang and Bo Zheng

32. ?Automated Self-Supervised Learning for Recommendation with Masked Graph Transformer

Lianghao Xia, Chao Huang, Chunzhen Huang, Kangyi Lin, Tao Yu and Ben Kao

33. ? Improving Recommendation Fairness via Data Augmentation

Lei Chen, Le Wu, Kun Zhang, Richang Hong, Defu Lian, Zhiqiang Zhang, Jun Zhou and Meng Wang

34. ?ColdNAS: Search to Modulate for User Cold-Start Recommendation

Shiguang Wu, Yaqing Wang, Qinghe Jing, Daxiang Dong, Quanming Yao and Dejing Dou

35. ?AutoS2AE: Automate to Regularize Sparse Shallow Autoencoders for Recommendation

Rui Fan, Jin Chen, Yuanhao Pu, Zhihao Zhu, Defu Lian and Enhong Chen

36. ?Quantize Sequential Recommenders Without Private Data

Lingfeng Shi, Yuang Liu, Jun Wang and Wei Zhang

37. Interaction-level Membership Inference Attack Against Federated Recommender Systems

Wei Yuan, Chaoqun Yang, Quoc Viet Hung Nguyen, Lizhen Cui, Tieke He and Hongzhi Yin

38. Contrastive Learning with Interest and Conformity Disentanglement for Sequential Recommendation

Yuhao Yang, Chao Huang, Lianghao Xia, Chunzhen Huang, Da Luo and Kangyi Lin

39. Clustered Embedding Learning for Large-scale Recommender Systems

Yizhou Chen, Guangda Huzhang, Qingtao Yu, Hui Sun, Heng-Yi Li, Jingyi Li, Yabo Ni, Anxiang Zeng, Han Yu and Zhiming Zhou

40. Adap-: Adpatively Modulating Embedding Magnitude for Recommendation

Jiawei Chen, Junkang Wu, Jiancan Wu, Xuezhi Cao, Sheng Zhou and Xiangnan He

41. Robust Preference-Guided Denoising for Graph based Social Recommendation

Yuhan Quan, Jingtao Ding, Chen Gao, Lingling Yi, Depeng Jin and Yong Li

42. MMMLP: Multi-modal Multilayer Perceptron for sequence recommendation

Jiahao Liang, Xiangyu Zhao, Muyang Li, Zijian Zhang, Haochen Liu and Liu Zitao

43. Response-act Guided Reinforced Dialogue Generation for Mental Health Counseling

Aseem Srivastava, Ishan Pandey, Md Shad Akhtar and Tanmoy Chakraborty

44. Few-shot News Recommendation via Cross-lingual Transfer

Taicheng Guo, Lu Yu, Basem Shihada and Xiangliang Zhang

45. User Retention-oriented Recommendation with Decision Transformer

Kesen Zhao, Lixin Zou, Xiangyu Zhao, Maolin Wang and Dawei Yin

46. Cooperative Retriever and Ranker in Deep Recommenders

Xu Huang, Defu Lian, Jin Chen, Liu Zheng, Xing Xie and Enhong Chen

47. Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders

Yupeng Hou, Zhankui He, Julian McAuley and Wayne Xin Zhao

48. Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders

Yupeng Hou, Zhankui He, Julian McAuley and Wayne Xin Zhao

49. Show Me The Best Outfit for A Certain Scene: A Scene-aware Fashion Recommender System

Tangwei Ye, Liang Hu, Qi Zhang, Zhong Yuan Lai, Usman Naseem and Dora D. Liu

50. Multi-Behavior Recommendation with Cascading Graph Convolutional Network

Zhiyong Cheng, Sai Han, Fan Liu, Lei Zhu, Zan Gao and Yuxin Peng

51. ?AutoMLP: Automated MLP for Sequential Recommendations

Muyang Li, Zijian Zhang, Xiangyu Zhao, Minghao Zhao, Runze Wu and Ruocheng Guo

52. ?NASRec: Weight Sharing Neural Architecture Search for Recommender Systems

Tunhou Zhang, Dehua Cheng, Yuchen He, Zhengxing Chen, Xiaoliang Dai, Liang Xiong, Feng Yan, Hai Li, Yiran Chen and Wei Wen

53. ?Membership Inference Attacks Against Sequential Recommender Systems

Zhihao Zhu, Chenwang Wu, Rui Fan, Defu Lian and Enhong Chen

54. ?Communicative MARL-based Relevance Discerning Network for Repetition-Aware Recommendation

Kaiyuan Li, Pengfei Wang, Haitao Wang, Qiang Liu, Xingxing Wang, Dong Wang and Shangguang Wang

55. ?Invariant Collaborative Filtering to Popularity Distribution Shift

An Zhang, Jingnan Zheng, Xiang Wang, Yancheng Yuan and Tat-Seng Chua

56. ?Modeling Temporal Positive and Negative Excitation for Sequential Recommendation

Chengkai Huang, Shoujin Wang, Xianzhi Wang and Lina Yao

57. ?Personalized Graph Signal Processing for Collaborative Filtering

Jiahao Liu, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Li Shang and Ning Gu

58. ?Multi-Task Recommendations with Reinforcement Learning

Ziru Liu, Jiejie Tian, Qingpeng Cai, Xiangyu Zhao, Jingtong Gao, Shuchang Liu, Dayou Chen, Tonghao He, Dong Zheng, Peng Jiang and Kun Gai

59. ?A Self-Correcting Sequential Recommender

Yujie Lin, Chenyang Wang, Zhumin Chen, Zhaochun Ren, Xin Xin, Qiang Yan, Maarten de Rijke, Xiuzhen Cheng and Pengjie Ren

60. ?Cross-domain Recommendation with Behavioral Importance Perception

Hong Chen, Xin Wang, Ruobing Xie, Yuwei Zhou and Wenwu Zhu

61. ?Balancing Unobserved Confounding with a Few Unbiased Ratings in Debiased Recommendations

Haoxuan Li, Yanghao Xiao, Chunyuan Zheng and Peng Wu

62. ?Code Recommendation for Open Source Software Developers

Yiqiao Jin, Yunsheng Bai, Yanqiao Zhu, Yizhou Sun and Wei Wang

63. ?Denoising and Prompt-Tuning for Multi-Behavior Recommendation

Chi Zhang, Xiangyu Zhao, Rui Chen, Qilong Han and Li Li

64. ?Mutual Wasserstein Discrepancy Minimization for Sequential Recommendation

Ziwei Fan, Zhiwei Liu, Hao Peng and Philip S Yu

65. ?Confident Action Decision via Hierarchical Policy Learning for Conversational Recommendation

Heeseon Kim, Hyeongjun Yang and Kyong-Ho Lee

66. ?CAMUS: Attribute-Aware Counterfactual Augmentation for Minority Users in Recommendation

Yuxin Ying, Fuzhen Zhuang, Yongchun Zhu, Deqing Wang and Hongwei Zheng

67. Dynamically Expandable Graph Convolution for Streaming Recommendation

Bowei He, Xu He, Yingxue Zhang, Ruiming Tang and Chen Ma

68. Dual Policy Learning for Aggregation Optimization in Recommender Systems

Heesoo Jung, Hogun Park and Sangpil Kim

69. Automatic Feature Selection By One-Shot Neural Architecture Search In Recommendation Systems

Haiyang Wu, He Wei, Yuekui Yang, Yangyang Tang, Meixi Liu and Jianfeng Li

70. Semi-supervised Adversarial Learning for Complementary Item Recommendation

Koby Bibas, Oren Sar Shalom and Dietmar Jannach

71. Towards Explainable Collaborative Filtering with Taste Clusters Learning

Yuntao Du, Jianxun Lian, Jing Yao, Xiting Wang, Mingqi Wu, Lu Chen, Yunjun Gao and Xing Xie

72. Towards Explainable Collaborative Filtering with Taste Clusters Learning

Yuntao Du, Jianxun Lian, Jing Yao, Xiting Wang, Mingqi Wu, Lu Chen, Yunjun Gao and Xing Xie

SIGIR 2023

1. Poisoning Self-supervised Learning Based Sequential Recommendations

Yanling Wang, Yuchen Liu, Qian Wang, Cong Wang and Chenliang Li

2. M2GNN: Metapath and Multi-interest Aggregated Graph Neural Network for Tag-based Cross-domain Recommendation

Zepeng Huai, Yuji Yang, Mengdi Zhang, Zhongyi Zhang, Yichun Li and Wu Wei

3. EulerNet: Adaptive Feature Interaction Learning via Eulers Formula for CTR Prediction

Zhen Tian, Ting Bai, Wayne Xin Zhao, Ji-Rong Wen and Zhao Cao

4. Continuous Input Embedding Size Search For Recommender Systems

Yunke Qu, Tong Chen, Xiangyu Zhao, Lizhen Cui, Kai Zheng and Hongzhi Yin

5. A Preference Learning Decoupling Framework for User Cold-Start Recommendation

Chunyang Wang, Yanmin Zhu, Aixin Sun, Zhaobo Wang and Ke Wang

6. Prompt Learning for News Recommendation

Zizhuo Zhang and Bang Wang

7. Multi-view Multi-aspect Neural Networks for Next-basket Recommendation

Zhiying Deng, Jianjun Li, Zhiqiang Guo, Wei Liu, Li Zou and Guohui Li

8. Strategy-aware Bundle Recommender System

Yinwei Wei, Xiaohao Liu, Yunshan Ma, Xiang Wang, Liqiang Nie and Tat-Seng Chua

9. Knowledge-enhanced Multi-View Graph Neural Networks for Session-based Recommendation

Qian Chen, Zhiqiang Guo, Jianjun Li and Guohui Li

10. Exploring scenarios of uncertainty about the users preferences in interactive recommendation systems

Ncollas Silva, Thiago Silva, Henrique Hott, Yan Ribeiro, Adriano Pereira and Leonardo Rocha

11. Topic-enhanced Graph Neural Networks for Extraction-based Explainable Recommendation

Jie Shuai, Le Wu, Kun Zhang, Peijie Sun, Richang Hong and Meng Wang

12. Instance Transfer for Cross-Domain Recommendations

Jingtong Gao, Xiangyu Zhao, Bo Chen, Fan Yan, Huifeng Guo and Ruiming Tang

13. EEDN: Enhanced Encoder-Decoder Network with Local and Global Context Learning for POI Recommendation

Xinfeng Wang, Fumiyo Fukumoto, Jin Cui, Yoshimi Suzuki, Jiyi Li and Dongjin Yu

14. Generative-Contrastive Graph Learning for Recommendation

Yonghui Yang, Zhengwei Wu, Le Wu, Kun Zhang, Richang Hong, Zhiqiang Zhang, Jun Zhou and Meng Wang

15. Time-interval Aware Share Recommendation via Bi-directional Continuous Time Dynamic Graphs

Ziwei Zhao, Xi Zhu, Tong Xu, Aakas Lizhiyu, Yu Yu, Xueying Li, Zikai Yin and Enhong Chen

16. Multi-behavior Self-supervised Learning for Recommendation

Jingcao Xu, Chaokun Wang, Cheng Wu, Yang Song, Kai Zheng, Xiaowei Wang, Changping Wang, Guorui Zhou and Kun Gai

17. MELT: Mutual Enhancement of Long-Tailed User and Item for Sequential Recommendation

Kibum Kim, Dongmin Hyun, Sukwon Yun and Chanyoung Park

18. Single-shot Feature Selection Framework for Multi-task Deep Recommender Systems

Yejing Wang, Zhaocheng Du, Xiangyu Zhao, Bo Chen, Huifeng Guo, Ruiming Tang and Zhenhua Dong

19. Editable User Profiles for Controllable Text Recommendations

Sheshera Mysore, Mahmood Jasim, Andrew Mccallum and Hamed Zamani

20. Intent-aware Ranking Ensemble for Personalized Recommendation

Jiayu Li, Peijie Sun, Zhefan Wang, Weizhi Ma, Yangkun Li, Min Zhang, Zhoutian Feng and Daiyue Xue

21. RCENR: A Reinforced and Contrastive Heterogeneous Network Reasoning Model for Explainable News Recommendation

Hao Jiang, Chuanzhen Li, Juanjuan Cai and Jingling Wang

22. Candidateaware Graph Contrastive Learning for Recommendation

Wei He, Guohao Sun, Jinhu Lu and Xiu Susie Fang

23. LightGT: A Light Graph Transformer for Multimedia Recommendation

Yinwei Wei, Wenqi Liu, Fan Liu, Xiang Wang, Liqiang Nie and Tat-Seng Chua

24. AdaMCL: Adaptive Fusion Multi-View Contrastive Learning for Collaborative Filtering

Guanghui Zhu, Wang Lu, Chunfeng Yuan and Yihua Huang

25. Mixed-Curvature Manifolds Interaction Learning for Knowledge Graph-aware Recommendation

Jihu Wang, Yuliang Shi, Han Yu, Xinjun Wang, Zhongmin Yan and Fanyu Kong

26. Multimodal Counterfactual Learning Network for Multimedia-based Recommendation

Shuaiyang Li, Dan Guo, Kang Liu, Richang Hong and Feng Xue

27. Beyond Two-Tower Matching: Learning Sparse Retrievable Interaction Models for Recommendation

Liangcai Su, Fan Yan, Jieming Zhu, Xi Xiao, Haoyi Duan, Zhou Zhao, Zhenhua Dong and Ruiming Tang

28. HDNR: A Hyperbolic-Based Debiased Approach for Personalized News Recommendation

Shicheng Wang, Shu Guo, Lihong Wang, Tingwen Liu and Hongbo Xu

29. Adaptive Graph Representation Learning for Next POI Recommendation

Zhaobo Wang, Yanmin Zhu, Chunyang Wang, Wenze Ma, Bo Li and Jiadi Yu

30. Alleviating Matthew Effect of Offline Reinforcement Learning in Recommendation

Chongming Gao, Kexin Huang, Jiawei Chen, Yuan Zhang, Biao Li, Peng Jiang, Shiqi Wang, Zhong Zhang and Xiangnan He

31. Spatio-Temporal Hypergraph Learning for Next POI Recommendation

Xiaodong Yan, Tengwei Song, Yifeng Jiao, Jianshan He, Jiaotuan Wang, Ruopeng Li and Wei Chu

32. Knowledge-refined Denoising Network for Robust Recommendation

Xinjun Zhu, Yuntao Du, Yuren Mao, Lu Chen, Yujia Hu and Yunjun Gao

33. Distillation-Enhanced Graph Masked Autoencoders for Bundle Recommendation

Yuyang Ren, Zhang Haonan, Luoyi Fu, Xinbing Wang and Chenghu Zhou

34. Distributionally Robust Sequential Recommendation

Rui Zhou, Xian Wu, Zhaopeng Qiu, Yefeng Zheng and Xu Chen

35. Reformulating CTR Prediction: Learning Invariant Feature Interactions for Recommendation

Yang Zhang, Tianhao Shi, Fuli Feng, Wenjie Wang, Dingxian Wang, Xiangnan He and Yongdong Zhang

36. Model-agnostic Behavioral Distillation For Cold-start Item Recommendation

Zefan Wang, Hao Chen, Xiao Huang, Yufeng Qian, Zhetao Li and Feiran Huang

37. Measuring Item Global Residual Value for Fair Recommendation

Jiayin Wang, Weizhi Ma, Chumeng Jiang, Min Zhang, Yuan Zhang, Biao Li and Peng Jiang

38. Curse of Low Dimensionality in Recommender Systems

Naoto Ohsaka and Riku Togashi

39. Its Enough: Relaxing Diagonal Constraints in Regression-based Linear Recommender Models

Jaewan Moon, Hye Young Kim and Jongwuk Lee

40. Beyond the Overlapping Users: Cross-Domain Recommendation via Adaptive Anchor Link Learning

Yi Zhao, Chaozhuo Li, Jiquan Peng, Xiaohan Fang, Feiran Huang, Senzhang Wang, Xing Xie and Jibing Gong

41. LOAM: Improving Long-tail Session-based Recommendation via Niche Walk Augmentation and Tail Session Mixup

Heeyoon Yang, Gahyung Kim, Jee-Hyong Lee and YunSeok Choi

42. Diffusion Recommender Model

Wenjie Wang, Yiyan Xu, Fuli Feng, Xinyu Lin, Xiangnan He and Tat-Seng Chua

43. Causal Decision Transformer for Recommender Systems via Offline Reinforcement Learning

Siyu Wang, Xiaocong Chen, Lina Yao and Dietmar Jannach

44. Hydrus: Improving Quality of Experience in Recommendation Systems by Making Latency-Accuracy Tradeoffs

Zhiyu Yuan, Kai Ren, Gang Wang and Xin Miao

45. Manipulating Federated Recommender Systems: Poisoning with Synthetic Users and Its Countermeasures

Wei Yuan, Quoc Viet Hung Nguyen, Tieke He, Liang Chen and Hongzhi Yin

46. Contrastive State Augmentations for Reinforcement Learning-Based Recommender Systems

Zhaochun Ren, Na Huang, Yidan Wang, Pengjie Ren, Jun Ma, Jiahuan Lei, Xinlei Shi, Hengliang Luo, Joemon Jose and Xin Xin

47. Multi-view Hypergraph Contrastive Policy Learning for Conversational Recommendation

Sen Zhao, Wei Wei, Xian-Ling Mao, Shuai Zhu, Minghui Yang, Zujie Wen, Dangyang Chen and Feida Zhu

48. Rectifying Unfairness in Recommendation Feedback Loop

Mengyue Yang, Jun Wang and Jean-Francois Ton

49. Next Basket Recommendation with Intent-aware Hypergraph Adversarial Network

Ran Li, Liang Zhang, Guannan Liu and Junjie Wu

50. Masked Graph Transformer for Recommendation

Chaoliu Li, Chao Huang, Lianghao Xia, Xubin Ren, Yaowen Ye and Yong Xu

51. Improving Implicit Feedback-Based Recommendation through Multi-Behavior Alignment

Xin Xin, Xiangyuan Liu, Hanbing Wang, Pengjie Ren, Zhumin Chen, Jiahuan Lei, Xinlei Shi, Hengliang Luo, Joemon Jose, Maarten de Rijke and Zhaochun Ren

52. PLATE: A Prompt-enhanced Paradigm for Multi-Target Cross-Domain Recommendation

Yuhao Wang, Xiangyu Zhao, Bo Chen, Qidong Liu, Huifeng Guo, Huanshuo Liu, Yichao Wang, Rui Zhang and Ruiming Tang

53. Disentangled Contrastive Collaborative Filtering

Xubin Ren, Chao Huang, Lianghao Xia, Jiashu Zhao and Dawei Yin

54. Ensemble Modeling with Contrastive Knowledge Distillation for Sequential Recommendation

Hanwen Du, Huanhuan Yuan, Pengpeng Zhao, Fuzhen Zhuang, Guanfeng Liu, Lei Zhao, Yanchi Liu and Victor S Sheng

55. Model-Agnostic Decentralized Collaborative Learning for On-Device POI Recommendation

Jing Long, Tong Chen, Quoc Viet Hung Nguyen, Guandong Xu, Kai Zheng and Hongzhi Yin

56. M2EU: Meta Learning for Cold-start Recommendation via Enhancing User Preference Estimation

Zhenchao Wu and Xiao Zhou

57. Dynamic Graph Evolution Learning for Recommendation

Haoran Tang, Shiqing Wu, Guandong Xu and Qing Li

58. Linear Attention Mechanism for Long-term Sequential Recommender Systems

Langming Liu, Xiangyu Zhao, Chi Zhang, Jingtong Gao, Wanyu Wang, Wenqi Fan, Yiqi Wang, Ming He, Zitao Liu and Qing Li

59. Mining Stable Preferences: Adaptive Modality Decorrelation for Multimedia Recommendation

Jinghao Zhang, Qiang Liu, Shu Wu and Liang Wang

60. Graph Masked Autoencoder for Sequential Recommendation

Yaowen Ye, Chao Huang and Lianghao Xia

61. Wisdom of Crowds and Fine-Grained Learning for Serendipity Recommendations

Zhe Fu, Xi Niu and Li Yu

62. When Search Meets Recommendation: Learning Disentangled Search Representation for Recommendation

Zihua Si, Zhongxiang Sun, Xiao Zhang, Jun Xu, Xiaoxue Zang, Yang Song, Kun Gai and Ji-Rong Wen

63. Adaptive Popularity Debiasing Aggregator for Graph Collaborative Filtering

Huachi Zhou, Hao Chen, Junnan Dong, Daochen Zha, Chuang Zhou and Xiao Huang

64. Meta-optimized Contrastive Learning for Sequential Recommendation

Xiuyuan Qin, Huanhuan Yuan, Pengpeng Zhao, Junhua Fang, Fuzhen Zhuang, Guanfeng Liu, Yanchi Liu and Victor Sheng

65. Triple Structural Information Modelling for Accurate, Explainable and Interactive Recommendation

Jiahao Liu, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Li Shang and Ning Gu

66. Blurring-Sharpening Process Models for Collaborative Filtering

Jeongwhan Choi, Seoyoung Hong, Noseong Park and Sung-Bae Cho

67. When Newer is Not Better: Does Deep Learning Really Benefit Recommendation From Implicit Feedback

Yushun Dong, Jundong Li and Tobias Schnabel

68. Dual Contrastive Transformer for Hierarchical Preference Modeling in Sequential Recommendation

Chengkai Huang, Shoujin Wang, Xianzhi Wang and Lina Yao

69. Learning Fine-grained User Interests for Micro-video Recommendation

Yu Shang, Chen Gao, Jiansheng Chen, Depeng Jin, Yong Li and Meng Wang

70. A Generic Learning Framework for Sequential Recommendation with Distribution Shifts

Zhengyi Yang, Xiangnan He, Jizhi Zhang, Jiancan Wu, Xin Xin, Jiawei Chen and Xiang Wang

71. Frequency Enhanced Hybrid Attention Network for Sequential Recommendation

Xinyu Du, Huanhuan Yuan, Pengpeng Zhao, Jianfeng Qu, Fuzhen Zhuang, Guanfeng Liu, Yanchi Liu and Victor S Sheng

72. Fine-Grained Preference-Aware Personalized Federated POI Recommendation with Data Sparsity

Xiao Zhang, Ziming Ye, Jianfeng Lu, Fuzhen Zhuang, Yanwei Zheng and Dongxiao Yu

73. News Popularity Beyond the Click-Through-Rate for Personalized Recommendations

Ashutosh Nayak, Mayur Garg and Rajasekhara Reddy Duvvuru Muni

https://sigir.org/sigir2023/program/accepted-papers/short-papers/

具体的短文推荐系统相关标题整理如下：

1. Mining Interest Trends and Adaptively Assigning Sample Weight for Session-based Recommendation

Kai Ouyang, Xianghong Xu, Miaoxin Chen, Zuotong Xie, Hai-Tao Zheng, Shuangyong Song and Yu Zhao

2. CEC: Towards Learning Global Optimized Recommendation through Causality Enhanced Conversion Model

Ran Le, Guoqing Jiang, Xiufeng Shu, Ruidong Han, Qianzhong Li, Yacheng Li, Xiang Li and Wei Lin

3. Computational Versus Perceived Popularity Miscalibration in Recommender Systems

Oleg Lesota, Gustavo Escobedo, Yashar Deldjoo, Bruce Ferwerda, Simone Kopeinik, Elisabeth Lex, Navid Rekabsaz and Markus Schedl

4. Always Strengthen Your Strengths: A Drift-Aware Incremental Learning Framework for CTR Prediction

Congcong Liu, Fei Teng, Xiwei Zhao, Zhangang Lin, Jinghe Hu and Jingping Shao

5. Quantifying and Leveraging User Fatigue for Interventions in Recommender Systems

Hitesh Sagtani, Madan Gopal Jhawar, Akshat Gupta and Rishabh Mehrotra

6. ADL: Adaptive Distribution Learning Framework for Multi-Scenario CTR Prediction

Jinyun Li, Huiwen Zheng, Yuanlin Liu, Minfang Lu, Lixia Wu and Haoyuan Hu

7. A Model-Agnostic Popularity Debias Training Framework for Click-Through Rate Prediction in Recommender System

Fan Zhang and Qijie Shen

8. Graph Collaborative Signals Denoising and Augmentation for Recommendation

Ziwei Fan, Ke Xu, Zhang Dong, Hao Peng, Jiawei Zhang and Philip S Yu

9. Denoise to protect: a method to robustify visual recommenders from adversaries

Felice Antonio Merra, Vito Walter Anelli, Tommaso Di Noia, Daniele Malitesta and Alberto Carlo Maria Mancino

10. Model-free Reinforcement Learning with Stochastic Reward Stabilization for Recommender Systems

Tianchi Cai, Shenliao Bao, Jiyan Jiang, Shiji Zhou, Wenpeng Zhang, Lihong Gu, Jinjie Gu and Guannan Zhang

11. Context-Aware Modeling via Simulated Exposure Page for CTR Prediction in Meituan Waimai

Xiang Li, Shuwei Chen, Jian Dong, Jin Zhang, Yongkang Wang, Xingxing Wang and Dong Wang

12. Review-based Multi-intention Contrastive Learning for Recommendation

Wei Yang, Tengfei Huo, Zhiqiang Liu and Chi Lu

13. Simplifying Content-Based Neural News Recommendation: On User Modeling and Training Objectives

Andreea Iana, Goran Glava and Heiko Paulheim

14. Personalized Dynamic Recommender System for Investors

Takehiro Takayanagi, Chung-Chi Chen and Kiyoshi Izumi

15. WSFE: Wasserstein Sub-graph Feature Encoder for Effective User Segmentation in Collaborative Filtering

Yankai Chen, Yifei Zhang, Menglin Yang, Zixing Song, Chen Ma and Irwin King

16. Hard Negative Mining with Neighborhood Similarity for Sequential Recommendation

Lu Fan, Jiashu Pu, Rongsheng Zhang and Xiao-Ming Wu

17. Personalized Showcases: Generating Multi-Modal Explanations for Recommendations

An Yan, Zhankui He, Jiacheng Li, Tianyang Zhang and Julian McAuley

18. Improving News Recommendation via Bottlenecked Multi-task Pre-training

Xiongfeng Xiao, Qing Li, Songlin Liu and Kun Zhou

19. Attention Mixtures for Time-Aware Sequential Recommendation

Viet Anh Tran, Guillaume Salha-Galvan, Bruno Sguerra and Romain Hennequin

20. Sharpness-Aware Graph Collaborative Filtering

Huiyuan Chen, Chin-Chia Michael Yeh, Yujie Fan, Yan Zheng, Junpeng Wang, Vivian Lai, Mahashweta Das and Hao Yang

21. Connecting Unseen Domains: Cross-Domain Invariant Learning in Recommendation

Yang Zhang, Yue Shen, Dong Wang, Jinjie Gu and Guannan Zhang

22. Unbiased Pairwise Learning from Implicit Feedback for Recommender Systems without Biased Variance Control

Yi Ren, Hongyan Tang, Jiangpeng Rong and Siwen Zhu

23. Uncertainty-aware Consistency Learning for Cold-Start Item Recommendation

Taichi Liu, Chen Gao, Zhenyu Wang, Dong Li, Jianye Hao, Depeng Jin and Yong Li

24. Rows or Columns Minimizing Presentation Bias When Comparing Multiple Recommender Systems

Patrik Dokoupil, Ladislav Peska and Ludovico Boratto

25. uCTRL: Unbiased Contrastive Representation Learning via Alignment and Uniformity for Collaborative Filtering

Jae-woong Lee, Seongmin Park, Mincheol Yoon and Jongwuk Lee

26. Forget Me Now: Fast and Exact Unlearning in Neighborhood-based Recommendation

Sebastian Schelter, Mozhdeh Ariannezhad and Maarten de Rijke

27. Robust Causal Inference for Recommender System to Overcome Noisy Confounders

Zhiheng Zhang, Quanyu Dai, Xu Chen, Zhenhua Dong and Ruiming Tang

28. LogicRec: Recommendation with Users Logical Requirements

Zhenwei Tang, Griffin Floto, Armin Toroghi, Shichao Pei, Xiangliang Zhang and Scott Sanner

29. Attention-guided Multi-step Fusion: A Hierarchical Fusion Network for Multimodal Recommendation

Yan Zhou, Jie Guo, Hao Sun, Bin Song and Fei Richard Yu

30. User-Dependent Learning to Debias for Recommendation

Fangyuan Luo and Jun Wu

31. TAML: Time-Aware Meta Learning for Cold-Start Problem in News Recommendation

Jingyuan Li, Yue Zhang, Xuan Lin, Xinxing Yang, Ge Zhou, Longfei Li, Hong Chen and Jun Zhou

32. The Dark Side of Explanations: Poisoning Recommender Systems with Counterfactual Examples

Ziheng Chen, Jia Wang, Gabriele Tolomei, Fabrizio Silvestri and Yongfeng Zhang

33. Prediction then Correction: An Abductive Prediction Correction Method for Sequential Recommendation

Yang Zhang, Yulong Huang, Qifan Wang, Chenxu Wang and Fuli Feng

34. Attacking Pre-trained Recommendation

Yiqing Wu, Ruobing Xie, Zhao Zhang, Yongchun Zhu, Fuzhen Zhuang, Jie Zhou, Yongjun Xu and Qing He

35. FINAL:Factorized Interaction Layer for CTR Prediction

Jieming Zhu, Qinglin Jia, Guohao Cai, Quanyu Dai, Jingjie Li, Zhenhua Dong, Ruiming Tang and Rui Zhang

36. Inference at Scale: Significance Testing for Large Search and Recommendation Experiments

Ngozi Ihemelandu and Michael D Ekstrand

37. Causal Disentangled Variational Auto-Encoder for Preference Understanding in Recommendation

Siyu Wang, Xiaocong Chen, Quan Z Sheng, Yihong Zhang and Lina Yao

38. Allocate According to Potential: Towards a Win-Win Recommendation for Popularity Debias and Performance Boost

Yuanhao Liu, Qi Cao, Huawei Shen, Yunfan Wu, Shuchang Tao and Xueqi Cheng

39. Uncertainty-based Heterogeneous Privileged Knowledge Distillation for Recommendation System

Ang Li, Jian Hu, Ke Ding, Xiaolu Zhang, Jun Zhou, Yong He and Xu Min

40. Optimizing Reciprocal Rank with Bayesian Average for improved Next Item Recommendation

Xiangkui Lu, Jun Wu and Jianbo Yuan

KDD 2023

1. Efficient and Joint Hyperparameter and Architecture Search for Collaborative Filtering
2. Improving Conversational Recommendation Systems via Counterfactual Data Simulation
3. LATTE: A Framework for Learning Item-Features to Make a Domain-Expert for Effective Conversational Recommendation
4. User-Regulation Deconfounded Conversational Recommender System with Bandit Feedback
5. Path-Specific Counterfactual Fairness for Recommender Systems
6. Meta multi-agent exercise recommendation: A game application perspective
7. Shilling Black-box Review-based Recommender Systems through Fake Review Generation
8. Generalized Matrix Local Low Rank Representation by Random Projection and Submatrix Propagation
9. Privacy Matters: Vertical Federated Linear Contextual Bandits for Privacy Protected Recommendation
10. Off-Policy Evaluation of Ranking Policies under Diverse User Behavior
11. Generative Flow Network for Listwise Recommendation
12. Text Is All You Need: Learning Language Representations for Sequential Recommendation
13. MAP: A Model-agnostic Pretraining Framework for Click-through Rate Prediction
14. Cognitive Evolutionary Search to Select Feature Interactions for Click-Through Rate Prediction
15. PrefRec: Recommender Systems with Human Preferences for Reinforcing Long-term User Engagement
16. Efficient Bi-Level Optimization for Recommendation Denoising
17. Adaptive Disentangled Transformer for Sequential Recommendation
18. Meta Graph Learning for Long-tail Recommendation
19. Graph Neural Bandits
20. E-commerce Search via Content Collaborative Graph Neural Network
21. Criteria Tell you More than Ratings: Criteria Preference-Aware Light Graph Convolution for Effective Multi-Criteria Recommendation
22. Knowledge Graph Self-Supervised Rationalization for Recommendation
23. On Manipulating Signals of User-Item Graph: A Jacobi Polynomial-based Graph Collaborative Filtering
24. Impatient Bandits: Optimizing Recommendations for the Long-Term Without Delay
25. Hierarchical Invariant Learning for Domain Generalization Recommendation
26. UCEpic: Unifying Aspect Planning and Lexical Constraints for Generating Explanations in Recommendation
27. Debiasing Recommendation by Learning Identifiable Latent Confounders
28. Reconsidering Learning Objectives in Unbiased Recommendation: A Distribution Shift Perspective
29. Who should be Given Incentives? Counterfactual Optimal Treatment Regimes Learning for Recommendation
30. Unbiased Delayed Feedback Label Correction for Conversion Rate Prediction
31. A Sublinear Time Algorithm for Opinion Optimization in Directed Social Networks via Edge Recommendation
32. Multiplex Heterogeneous Graph Neural Network with Behavior Pattern Modeling
33. Contrastive Learning for User Sequence Representation in Personalized Product Search
34. Empowering General-purpose User Representation with Full-life Cycle Behavior Modeling
35. Task Relation-aware Continual User Representation Learning

CIKM 2023

文章来源:https://blog.csdn.net/weiwei935707936/article/details/132601701
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