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第46届SIGIR2023会议（ACM国际信息检索大会），将于2023年7月23日-7月27日在中国台湾台北召开。SIGIR是中国计算机学会CCF推荐的A类国际学术会议，也是人工智能领域智能信息检索方向最权威的国际会议。这次会议共收到822篇长文投稿，仅有165篇长文被录用，长文录用率约20.1%。另外，共收到短文613篇，仅154篇录用，短文接收率为25.12%。

最近，SIGIR官网公布了论文接收列表，并将论文分为了长文、短文、观点类论文、复现型论文、资源型论文演示论文、工业界论文、博士论坛论文等。其中，在165篇长文中有大约73篇推荐系统相关论文，在154篇短文中大概有40篇左右推荐系统相关论文。下文将整理这两大类中的推荐系统相关论文，更多论文请查看官网链接。

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

在所接收的长文中，推荐系统相关话题主要包括序列推荐、跨域推荐、点击率预估、推荐中的自动机器学习、冷启动推荐、新闻推荐、捆绑推荐、会话推荐、可解释推荐等。

所涵盖的技术包括自监督学习、图神经网络、参数搜索、多任务学习、扩散技术、因果推断、Transformer等技术。

具体的长文推荐系统相关标题整理如下：

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

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