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
