2023 推荐系统论文整理
2023 推荐系统论文整理
对2023年的 推荐系统论文进行一波收集，给各位初学者和算法大佬作为灵感来源，后续专栏会继续更新论文解读，根据评论不断补充，欢迎大家三连~
ICLR 2023
转载自：https://zhuanlan.zhihu.com/p/571454232
ICLR 2023 传送门：https://openreview.net/group?id=ICLR.cc/2023/Conference
今年ICLR里推荐系统相关的文章还是不少，以下是整理的论文列表，给各位工程师下半年的KPI提供灵感：
- Recommender Transformers with Behavior Pathways
一种叫做Pathway Attention 的 Transformer (RETR)。 RETR 可以动态规划为每个用户指定的行为路径，有点类似hard attention。
- IEDR: A Context-aware Intrinsic and Extrinsic Disentangled Recommender
- System
通过两个组件：对比学习组件和分解组件从各种上下文中学习内在和外在因素进行推荐
- Multi-Behavior Dynamic Contrastive Learning for Recommendation
设计了一种具有异构短期和长期兴趣建模的多行为对比学习范式
- Everyone’s Preference Changes Differently: Weighted Multi-Interest Retrieval Model
多兴趣偏好（MIP）模型，该方法不仅通过更有效地利用用户的顺序参与为用户产生多兴趣，而且自动学习一组权重来表示对每个嵌入的偏好以便可以按比例从每个兴趣中检索候选集。
- Consistent Data Distribution Sampling for Large-scale Retrieval
新的负采样策略，使用相对大规模的统一训练负样本和批量负样本来分别充分训练长尾和热门项目，并使用高发散负样本来提高学习收敛性。
- MaskFusion: Feature Augmentation for Click-Through Rate Prediction via Input-adaptive Mask Fusion
称为MaskFusion 的自适应特征融合框架，输入特征和深层结构(dnn之类的)交互融合。
- Deep Evidential Reinforcement Learning for Dynamic Recommendations
- Simple Yet Effective Graph Contrastive Learning for Recommendation
- Recommendation with User Active Disclosing Willingness
- Communication Efficient Fair Federated Recommender System
- Explainable Recommender with Geometric Information Bottleneck
- TGP: Explainable Temporal Graph Neural Networks for Personalized Recommendation
- TDR-CL: Targeted Doubly Robust Collaborative Learning for Debiased Recommendations
- Where to Go Next for Recommender Systems? ID- vs. Modality-based recommender models revisited
- Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems
- Inverse Learning with Extremely Sparse Feedback for Recommendation
- Personalized Reward Learning with Interaction-Grounded Learning (IGL)
- StableDR: Stabilized Doubly Robust Learning for Recommendation on Data Missing Not at Random
- Has It Really Improved? Knowledge Graph Based Separation And Fusion For Recommendation
- ResAct: Reinforcing Long-term Engagement in Sequential Recommendation with Residual Actor
- Clustering Embedding Tables, Without First Learning Them
结合hash和聚类压缩embedding - Dual personalization for federated recommendation on devices
- Enhancing Cross-Category Learning in Recommendation Systems with Multi-Layer Embedding Training
- Neural Collaborative Filtering Bandits via Meta Learning
- Training via Confidence Ranking
WSDM
转载自： https://zhuanlan.zhihu.com/p/582742341
【哈工程】Disentangled Negative Sampling for Collaborative Filtering【解耦负采样的协同过滤】
【新南威尔士】IDNP: Interest Dynamics Modeling using Generative Neural Processes for Sequential Recommendation【IDNP：使用生成神经过程进行序列推荐的兴趣动态建模】
【上交，移动】Learning to Distinguish Multi-User Coupling Behaviors for TV Recommendation【学习区分电视推荐中的多用户耦合行为】
【阿尔伯塔，腾讯】One for All, All for One: Learning and Transferring User Embeddings for Cross-Domain Recommendation【迁移学习跨域推荐】
【腾讯】Slate-Aware Ranking for Recommendation
【南航】Knowledge Enhancement for Contrastive Multi-Behavior Recommendation【对比多行为推荐系统】
【字节】Disentangled Representation for Diversified Recommendations【多样性推荐中解耦表征】
【人大】Cognition-aware Knowledge Graph Reasoning for Explainable Recommendation【可解释推荐的认知知识图推理】
【中山】Self-Supervised Group Graph Collaborative Filtering for Group Recommendation【群组推荐的自监督群图协同过滤】
【spotify】Calibrated Recommendations as a Maximum Flow Problem【作为最大流量问题的校准化推荐】
【北大，美团】DisenPOI: Disentangling Sequential and Geographical Influence for Point-of-Interest Recommendation【DisenPOI：解耦POI推荐中序列和地理的影响】
【天大】Multi-Intentions Oriented Contrastive Learning for Sequential Recommendation【面向多意图的序列推荐对比学习】
【南大，阿里】MUSENET: Multi-Scenario Learning for Repeat-Aware Personalized Recommendation【MUSENET：重复感知的个性化推荐的多场景学习】
【阿姆斯特丹大学】A Personalized Neighborhood-based Model for Within-basket Recommendation in Grocery Shopping【杂货店购物篮内推荐的个性化邻域模型】
【悉尼科技大学】SGCCL: Siamese Graph Contrastive Consensus Learning for Personalized Recommendation【SGCCL：用于个性化推荐的暹罗图对比共识学习】
【武大】Relation Preference oriented High-order Sampling for Recommendation【面向关系偏好的高阶采样】
【山大】Variational Reasoning over Incomplete Knowledge Graphs for Conversational Recommendation【会话推荐中不完全知识图的变分推理】
【悉尼科技大学】Exploiting Explicit and Implicit Item relationships for Session-based Recommendation【利用基于会话的推荐的显式和隐式商品关系】
Range Restricted Route Recommendation Based on Spatial Keyword【基于空间关键词的距离受限路径推荐】
【弗吉尼亚，京东】Meta Policy Learning for Cold-Start Conversational Recommendation【元学习做对话推荐的冷启动】
【港大，微软】Efficiently Leveraging Multi-level User Intent for Session-based Recommendation via Atten-Mixer Network【通过Atten Mixer网络有效利用多级用户意图进行基于会话的推荐】
【北大】Improving News Recommendation with Channel-Wise Dynamic Representations and Contrastive User Modeling【利用频道动态表征和对比用户模型改进新闻推荐】
【悉尼科技大学，ebay】Simplifying Graph-based Collaborative Filtering for Recommendation【简化基于图的推荐协同过滤】
【上交，华为】AutoGen: An Automated Dynamic Model Generation Framework for Recommender System【AutoGen:推荐系统的自动动态模型生成框架】
【浙大，meta】A Causal View for Item-level Effect of Recommendation on User Preference【对用户偏好影响的因果分析】
【昆士兰，多家公司】Federated Unlearning for On-Device Recommendation【联邦unlearning】
【罗格斯】Explicit Counterfactual Data Augmentation for Recommendation【反事实数据增强推荐系统】
【康奈尔】Uncertainty Quantification for Fairness in Two-Stage Recommender Systems【两阶段推荐系统公平性的不确定性量化】
【伊利诺，字节】DGRec: Graph Neural Network for Recommendation with Diversified Embedding Generation【DGRec：具有多种embedding生成的用于推荐的图神经网络】
【中科大】Unbiased Knowledge Distillation for Recommendation【无偏知识蒸馏推荐系统】
【华中科技】VRKG4Rec: Virtual Relational Knowledge Graph for Recommendation【VRKG4Rec：用于推荐的虚拟关系知识图】
【阿里，北邮】Knowledge-Adaptive Contrastive Learning for Recommendation【知识自适应对比学习推荐系统】
【华南理工】Heterogeneous Graph Contrastive Learning for Recommendation【面向推荐的异构图对比学习】
【上交，华为】An F-shape Click Model for Information Retrieval on Multi-block Mobile Pages【多块移动页面信息检索的F形点击模型】
【人大，华为】Separating Examination and Trust Bias from Click Predictions for Unbiased Relevance Ranking【从点击预测中分离检查和信任偏差，进行无偏关联排序】
【复旦，微软】CL4CTR: A Contrastive Learning Framework for CTR Prediction【CL4CTR:CTR预测的对比学习框架】
【人大，腾讯】Directed Acyclic Graph Factorization Machines for CTR Prediction via Knowledge Distillation【基于知识提取的CTR预测的有向非循环图分解机】
AAAI
转载自：https://zhuanlan.zhihu.com/p/571454232
Fair Representation Learning for Recommendation: A Mutual Information Perspective 【推荐的公平表示学习：互信息的视角】
Untargeted Attack against Federated Recommendation Systems via Poisonous Item Embeddings and the Defense【通过有毒项目嵌入和防御对联邦推荐系统的无目标攻击】
PPGenCDR: A Stable and Robust Framework for Privacy-Preserving Cross-domain Recommendation 【PPGenCDR：一个稳定而鲁棒的隐私保护跨域推荐框架】
Adaptive Low-Precision Training for Embeddings in Click-Through Rate Prediction【点击率预测中嵌入的自适应低精度训练】
Factual and Informative Review Generation for Explainable Recommendation 【可解释推荐的事实和信息审查生成】
Cross-domain Adaptative Learning for Online Advertisement Customer Lifetime Value Prediction 【在线广告客户终身价值预测的跨域自适应学习】
Uniform Sequence Better: Time Interval Aware Data Augmentation for Sequential Recommendation 【更好的统一序列：用于序列推荐的时间间隔感知数据增强】
LANCER: A Lifetime-Aware News Recommender System 【LANCER：新闻推荐系统】
Context-aware Safe Medication Recommendations with Molecular Graph and DDI Graph Embedding【基于分子图和DDI图嵌入的上下文感知安全用药建议】
CP-Rec: Contextual Prompting for Conversational Recommender Systems 【CP Rec:会话推荐系统的上下文提示】
Multiple Robust Learning for Recommendation 【推荐的多重鲁棒学习】
Win-Win: A Privacy-Preserving Federated Framework for DualTarget Cross-Domain Recommendation 【双赢：双目标跨域推荐的隐私保护联邦框架】
Towards Reliable Item Sampling for Recommendation Evaluation 【推荐评估的可靠项目抽样】
Structure Aware Incremental Learning with Personalized Imitation Weights for Recommender Systems【基于个性化模仿权重的推荐系统结构感知增量学习】
CowClip: Reducing CTR Prediction Model Training Time from 12 hours to 10 minutes on 1 GPU 【CowClip：在1个GPU上将CTR预测模型训练时间从12小时减少到10分钟】
多任务
AdaTask: A Task-aware Adaptive Learning Rate Approach to Multitask Learning 【AdaTask：一种多任务学习的任务感知自适应学习率方法】
PiCor: Multi-Task Deep Reinforcement Learning with Policy Correction 【PiCor:多任务深度强化学习与策略修正】
Learning Conflict-Noticed Architecture for Multi-Task Learning 【基于学习冲突的多任务学习体系结构】
MIGA: A Unified Multi-task Generation Framework for Conversational Text-to-SQL 【MIGA：一个用于会话文本到SQL的统一多任务生成框架】
因果推断
Learning Instrumental Variable from Data Fusion for Treatment Effect Estimation 【用于干预效果评估的数据融合学习工具变量】
Knowledge-Bridged Causal Interaction Network for Causal Emotion Entailment 【基于知识桥的因果互动网络】
Estimating average causal effects from patient trajectories 【根据患者轨迹估计平均因果效应】
Disentangled Representation for Causal Mediation Analysis 【因果调解分析的离散表示】
Causal Inference with Conditional Instruments using Deep Generative Models 【使用深度生成模型的条件工具因果推断】
Robust Causal Graph Representation Learning against Confounding Effects 【抗混淆效应的鲁棒因果图表示学习】
Causal Recurrent Variational Autoencoder for Medical Time Series Generation 【用于医学时间序列生成的因果递归变分自动编码器】
Improvement-Focused Causal Recourse (ICR) 【基于改进的因果关系追索权（ICR）】
COCA: COllaborative CAusal Regularization for Audio-Visual Question Answering 【COCA：用于视听问答的协作因果规则化】
Direct Heterogeneous Causal Learning for Resource Allocation Problems in Marketing 【市场营销中资源分配问题的直接异质因果学习】
Self-supervised Learning for Multilevel Skeleton-based Forgery Detection via Temporal-Causal Consistency of Actions 【基于时间因果一致性的多级骨架伪造检测的自监督学习】
Causal Effect Identification in Cluster DAGs 【聚类DAG中因果关系的识别】
Learning Relational Causal Models with Cycles through Relational Acyclification 【通过关系非循环化学习具有循环的关系因果模型】
Weather2vec: Representation Learning for Causal Inference with Non-Local Confounding in Air Pollution and Climate Studies 【Weather2vec：空气污染和气候研究中非局部混淆因果推断的表征学习】
Counterfactual Dynamics Forecasting - A New Setting of Quantitative Reasoning 【反事实动力学预测——一种新的定量推理方法】
Video-Audio Domain Generalization via Confounder Disentanglement 【基于混淆因子解耦的视频音频域泛化】
Formalising the Robustness of Counterfactual Explanations for Neural Networks 【神经网络反事实解释的鲁棒性形式化】
Very Fast, Approximate Counterfactual Explanations for Decision Forests 【决策森林的快速近似反事实解释】
Counterfactual Learning with General Data-generating Policies 【反事实学习与一般数据生成策略】# 2023 推荐系统论文整理
WWW 2023
https://blog.csdn.net/abcdefg90876/article/details/129807190
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Submodular Maximization in the Presence of Biases with Applications to Recommendation
Anay Mehrotra and Nisheeth K. Vishnoi -
Scoping Fairness Objectives and Identifying Fairness Metrics for Recommender Systems: The Practitioners’ Perspective
Jessie J. Smith, Lex Beattie and Henriette Cramer -
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 -
Fairly Adaptive Negative Sampling for Recommendations
Xiao Chen, Wenqi Fan, Jingfan Chen, Haochen Liu, Zitao Liu, Qing Li and Zhaoxiang Zhang -
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 -
Collaboration-Aware Graph Convolutional Network for Recommender Systems
Yu Wang, Yuying Zhao, Yi Zhang and Tyler Derr -
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 -
ConsRec: Learning Consensus Behind Interactions for Group Recommendation
Xixi Wu, Yun Xiong, Yao Zhang, Yizhu Jiao, Jiawei Zhang, Yangyong Zhu and Philip Yu -
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 -
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 -
Intra and Inter Domain HyperGraph Convolutional Network for Cross-Domain Recommendation
Zhongxuan Han, Xiaolin Zheng, Chaochao Chen, Wenjie Cheng and Yang Yao -
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 -
ApeGNN: Node-Wise Adaptive Aggregation in GNNs for Recommendation
Dan Zhang, Yifan Zhu, Yuxiao Dong, Yuandong Wang, Wenzheng Feng, Evgeny Kharlamov and Jie Tang -
Enhancing User Personalization in Conversational Recommenders
Allen Lin, Ziwei Zhu, Jianling Wang and James Caverlee -
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 -
Multi-Modal Adversarial Self-Supervised Learning for Recommendation
Wei Wei, Chao Huang, Lianghao Xia and Chuxu Zhang -
Distillation from Heterogeneous Models for Top-K Recommendation
Seongku Kang, Wonbin Kweon, Dongha Lee, Jianxun Lian, Xing Xie and Hwanjo Yu -
On the Theories Behind Hard Negative Sampling for Recommendation
Wentao Shi, Jiawei Chen, Fuli Feng, Jizhi Zhang, Junkang Wu, Chongming Gao and Xiangnan He -
Fine-tuning Partition-aware Item Similarities for Efficient and Scalable Recommendation
Tianjun Wei, Jianghong Ma and Tommy W. S. Chow -
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 -
Bootstrap Latent Representations for Multi-modal Recommendation
Xin Zhou, Hongyu Zhou, Yong Liu, Zhiwei Zeng, Chunyan Miao, Pengwei Wang, Yuan You and Feijun Jiang -
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 -
Recommendation with Causality enhanced Natural Language Explanations
Jingsen Zhang, Xu Chen, Jiakai Tang, Weiqi Shao, Quanyu Dai, Zhenhua Dong and Rui Zhang -
Cross-domain recommendation via user interest alignment
Chuang Zhao, Hongke Zhao, Ming He, Jian Zhang and Jianping Fan -
A Simple Data-Augmented Framework For Smoothed Recommender System
Zhenlei Wang and Xu Chen -
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 -
Contrastive Collaborative Filtering for Cold-Start Item Recommendation
Zhihui Zhou, Lilin Zhang and Ning Yang -
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 -
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 -
A Counterfactual Collaborative Session-based Recommender System
Wenzhuo Song, Shoujin Wang, Yan Wang, Kunpeng Liu, Xueyan Liu and Minghao Yin -
Correlative Preference Transfer with Hierarchical Hypergraph Network for Multi-Domain Recommendation
Zixuan Xu, Penghui Wei, Shaoguo Liu, Weimin Zhang, Liang Wang and Bo Zheng -
Automated Self-Supervised Learning for Recommendation with Masked Graph Transformer
Lianghao Xia, Chao Huang, Chunzhen Huang, Kangyi Lin, Tao Yu and Ben Kao -
Improving Recommendation Fairness via Data Augmentation
Lei Chen, Le Wu, Kun Zhang, Richang Hong, Defu Lian, Zhiqiang Zhang, Jun Zhou and Meng Wang -
ColdNAS: Search to Modulate for User Cold-Start Recommendation
Shiguang Wu, Yaqing Wang, Qinghe Jing, Daxiang Dong, Quanming Yao and Dejing Dou -
AutoS2AE: Automate to Regularize Sparse Shallow Autoencoders for Recommendation
Rui Fan, Jin Chen, Yuanhao Pu, Zhihao Zhu, Defu Lian and Enhong Chen -
Quantize Sequential Recommenders Without Private Data
Lingfeng Shi, Yuang Liu, Jun Wang and Wei Zhang -
Interaction-level Membership Inference Attack Against Federated Recommender Systems
Wei Yuan, Chaoqun Yang, Quoc Viet Hung Nguyen, Lizhen Cui, Tieke He and Hongzhi Yin -
Contrastive Learning with Interest and Conformity Disentanglement for Sequential Recommendation
Yuhao Yang, Chao Huang, Lianghao Xia, Chunzhen Huang, Da Luo and Kangyi Lin -
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 -
Adap-: Adpatively Modulating Embedding Magnitude for Recommendation
Jiawei Chen, Junkang Wu, Jiancan Wu, Xuezhi Cao, Sheng Zhou and Xiangnan He -
Robust Preference-Guided Denoising for Graph based Social Recommendation
Yuhan Quan, Jingtao Ding, Chen Gao, Lingling Yi, Depeng Jin and Yong Li -
MMMLP: Multi-modal Multilayer Perceptron for sequence recommendation
Jiahao Liang, Xiangyu Zhao, Muyang Li, Zijian Zhang, Haochen Liu and Liu Zitao -
Response-act Guided Reinforced Dialogue Generation for Mental Health Counseling
Aseem Srivastava, Ishan Pandey, Md Shad Akhtar and Tanmoy Chakraborty -
Few-shot News Recommendation via Cross-lingual Transfer
Taicheng Guo, Lu Yu, Basem Shihada and Xiangliang Zhang -
User Retention-oriented Recommendation with Decision Transformer
Kesen Zhao, Lixin Zou, Xiangyu Zhao, Maolin Wang and Dawei Yin -
Cooperative Retriever and Ranker in Deep Recommenders
Xu Huang, Defu Lian, Jin Chen, Liu Zheng, Xing Xie and Enhong Chen -
Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders
Yupeng Hou, Zhankui He, Julian McAuley and Wayne Xin Zhao -
Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders
Yupeng Hou, Zhankui He, Julian McAuley and Wayne Xin Zhao -
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 -
Multi-Behavior Recommendation with Cascading Graph Convolutional Network
Zhiyong Cheng, Sai Han, Fan Liu, Lei Zhu, Zan Gao and Yuxin Peng -
AutoMLP: Automated MLP for Sequential Recommendations
Muyang Li, Zijian Zhang, Xiangyu Zhao, Minghao Zhao, Runze Wu and Ruocheng Guo -
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 -
Membership Inference Attacks Against Sequential Recommender Systems
Zhihao Zhu, Chenwang Wu, Rui Fan, Defu Lian and Enhong Chen -
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 -
Invariant Collaborative Filtering to Popularity Distribution Shift
An Zhang, Jingnan Zheng, Xiang Wang, Yancheng Yuan and Tat-Seng Chua -
Modeling Temporal Positive and Negative Excitation for Sequential Recommendation
Chengkai Huang, Shoujin Wang, Xianzhi Wang and Lina Yao -
Personalized Graph Signal Processing for Collaborative Filtering
Jiahao Liu, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Li Shang and Ning Gu -
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 -
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 -
Cross-domain Recommendation with Behavioral Importance Perception
Hong Chen, Xin Wang, Ruobing Xie, Yuwei Zhou and Wenwu Zhu -
Balancing Unobserved Confounding with a Few Unbiased Ratings in Debiased Recommendations
Haoxuan Li, Yanghao Xiao, Chunyuan Zheng and Peng Wu -
Code Recommendation for Open Source Software Developers
Yiqiao Jin, Yunsheng Bai, Yanqiao Zhu, Yizhou Sun and Wei Wang -
Denoising and Prompt-Tuning for Multi-Behavior Recommendation
Chi Zhang, Xiangyu Zhao, Rui Chen, Qilong Han and Li Li -
Mutual Wasserstein Discrepancy Minimization for Sequential Recommendation
Ziwei Fan, Zhiwei Liu, Hao Peng and Philip S Yu -
Confident Action Decision via Hierarchical Policy Learning for Conversational Recommendation
Heeseon Kim, Hyeongjun Yang and Kyong-Ho Lee -
CAMUS: Attribute-Aware Counterfactual Augmentation for Minority Users in Recommendation
Yuxin Ying, Fuzhen Zhuang, Yongchun Zhu, Deqing Wang and Hongwei Zheng -
Dynamically Expandable Graph Convolution for Streaming Recommendation
Bowei He, Xu He, Yingxue Zhang, Ruiming Tang and Chen Ma -
Dual Policy Learning for Aggregation Optimization in Recommender Systems
Heesoo Jung, Hogun Park and Sangpil Kim -
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 -
Semi-supervised Adversarial Learning for Complementary Item Recommendation
Koby Bibas, Oren Sar Shalom and Dietmar Jannach -
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 -
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
SIGIR2023
● A Critical Reexamination of Intra-List Distance and Dispersion
Naoto Ohsaka, Riku Togashi
● A Generic Learning Framework for Sequential Recommendation with Distribution Shifts
Zhengyi Yang, Xiangnan He, Jizhi Zhang, Jiancan Wu, Xin Xin, Jiawei Chen, Xiang Wang
● A Geometric Framework for Query Performance Prediction in Conversational Search
Guglielmo Faggioli, Nicola Ferro, Cristina Muntean, Raffaele Perego, Nicola Tonellotto
● A Personalized Dense Retrieval Framework for Unified Information Access
Hansi Zeng, Surya Kallumadi, Zaid Alibadi, Rodrigo Nogueira, Hamed Zamani
● A Preference Learning Decoupling Framework for User Cold-Start Recommendation
Chunyang Wang, Yanmin Zhu, Aixin Sun, Zhaobo Wang, Ke Wang
● A Scalable Framework for Automatic Playlist Continuation on Music Streaming Services
Walid Bendada, Guillaume Salha-Galvan, Thomas Bouabça, Tristan Cazenave
● A Symmetric Dual Encoding Dense Retrieval Framework for Knowledge-Intensive Visual Question Answering
Alireza Salemi, Juan Altmayer Pizzorno, Hamed Zamani
● A Topic-aware Summarization Framework with Different Modal Side Information
Xiuying Chen, Mingzhe Li, Shen Gao, Xin Cheng, Qiang Yang, Qishen Zhang, Xin Gao, Xiangliang Zhang
● A Unified Generative Retriever for Knowledge-Intensive Language Tasks via Prompt Learning
Jiangui Chen, Ruqing Zhang, Jiafeng Guo, Maarten De Rijke, Yiqun Liu, Yixing Fan, Xueqi Cheng
● AdaMCL: Adaptive Fusion Multi-View Contrastive Learning for Collaborative Filtering
Guanghui Zhu, Wang Lu, Chunfeng Yuan, Yihua Huang
● Adapting Generative Pretrained Language Model for Open-domain Multimodal Sentence Summarization
Dengtian Lin, Liqiang Jing, Xuemeng Song, Meng Liu, Teng Sun, Liqiang Nie
● Adaptive Graph Representation Learning for Next POI Recommendation
Zhaobo Wang, Yanmin Zhu, Chunyang Wang, Wenze Ma, Bo Li, Jiadi Yu
● Adaptive Popularity Debiasing Aggregator for Graph Collaborative Filtering
Huachi Zhou, Hao Chen, Junnan Dong, Daochen Zha, Chuang Zhou, Xiao Huang
● Alleviating Matthew Effect of Offline Reinforcement Learning in Interactive Recommendation
Chongming Gao, Kexin Huang, Jiawei Chen, Yuan Zhang, Biao Li, Peng Jiang, Shiqi Wang, Zhong Zhang, Xiangnan He
● An Effective Framework for Enhancing Query Answering in a Heterogeneous Data Lake
Qin Yuan, Ye Yuan, Zhenyu Wen, He Wang, Shiyuan Tang
● An Effective, Efficient, and Scalable Confidence-based Instance Selection Framework for Transformer-Based Text Classification
Washington Cunha, Celso França, Guilherme Fonseca, Leonardo Rocha, Marcos André Gonçalves
● An Offline Metric for the Debiasedness of Click Models
Romain Deffayet, Philipp Hager, Jean-Michel Renders, Maarten De Rijke
● Asymmetric Hashing for Fast Ranking via Neural Network Measures
Khoa Doan, Shulong Tan, Weijie Zhao, Ping Li
● Augmenting Low-Resource Text Classification with Graph-Grounded Pre-training and Prompting
Zhihao Wen, Yuan Fang
● 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, Jibing Gong
● 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, Ruiming Tang
● BLADE: Combining Vocabulary Pruning and Intermediate Pretraining for Scaleable Neural CLIR
Suraj Nair, Eugene Yang, Dawn Lawrie, James Mayfield, Douglas W. Oard
● Blurring-Sharpening Process Models for Collaborative Filtering
Jeongwhan Choi, Seoyoung Hong, Noseong Park, Sung-Bae Cho
● BotMoE: Twitter Bot Detection with Community-Aware Mixtures of Modal-Specific Experts
Yuhan Liu, Zhaoxuan Tan, Heng Wang, Shangbin Feng, Qinghua Zheng, Minnan Luo
● Candidate–aware Graph Contrastive Learning for Recommendation
Wei He, Guohao Sun, Jinhu Lu, Xiu Susie Fang
● Causal Decision Transformer for Recommender Systems via Offline Reinforcement Learning
Siyu Wang, Xiaocong Chen, Dietmar Jannach, Lina Yao
● Collaborative Residual Metric Learning
Tianjun Wei, Jianghong Ma, Tommy W.S. Chow
● Cone: Unsupervised Contrastive Opinion Extraction
Runcong Zhao, Lin Gui, Yulan He
● Constructing Tree-based Index for Efficient and Effective Dense Retrieval
Haitao Li, Qingyao Ai, Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Zheng Liu, Zhao Cao
● Continual Learning on Dynamic Graphs via Parameter Isolation
Peiyan Zhang, Yuchen Yan, Chaozhuo Li, Senzhang Wang, Xing Xie, Guojie Song, Sunghun Kim
● Continuous Input Embedding Size Search For Recommender Systems
Yunke Qu, Tong Chen, Xiangyu Zhao, Lizhen Cui, Kai Zheng, Hongzhi Yin
● Contrastive Box Embedding for Collaborative Reasoning
Tingting Liang, Yuanqing Zhang, Qianhui Di, Congying Xia, Youhuizi Li, Yuyu Yin
● Contrastive Learning for Signed Bipartite Graphs
Zeyu Zhang, Jiamou Liu, Kaiqi Zhao, Song Yang, Xianda Zheng, Yifei Wang
● 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, Xin Xin
● Creating a Silver Standard for Patent Simplification
Silvia Casola, Alberto Lavelli, Horacio Saggion
● Cross-Market Product-Related Question Answering
Negin Ghasemi, Mohammad Aliannejadi, Hamed Bonab, Evangelos Kanoulas, Arjen P. De Vries, James Allan, Djoerd Hiemstra
● Curse of “Low” Dimensionality in Recommender Systems
Naoto Ohsaka, Riku Togashi
● Data-Aware Proxy Hashing for Cross-modal Retrieval
Rong-Cheng Tu, Xian-Ling Mao, Wenjin Ji, Wei Wei, Heyan Huang
● Dataset Preparation for Arbitrary Object Detection: An Automatic Approach based on Web Information in English
Shucheng Li, Boyu Chang, Bo Yang, Hao Wu, Sheng Zhong, Fengyuan Xu
● Decoupled Hyperbolic Graph Attention Network for Cross-domain Named Entity Recognition
Jingyun Xu, Yi Cai
● Diffusion Recommender Model
Wenjie Wang, Yiyan Xu, Fuli Feng, Xinyu Lin, Xiangnan He, Tat-Seng Chua
● DisCover: Disentangled Music Representation Learning for Cover Song Identification
Jiahao Xun, Shengyu Zhang, Yanting Yang, Jieming Zhu, Liqun Deng, Zhou Zhao, Zhenhua Dong, Ruiqi Li, Lichao Zhang, Fei Wu
● Disentangled Contrastive Collaborative Filtering
Xubin Ren, Lianghao Xia, Jiashu Zhao, Dawei Yin, Chao Huang
● Distillation-Enhanced Graph Masked Autoencoders for Bundle Recommendation
Yuyang Ren, Zhang Haonan, Luoyi Fu, Xinbing Wang, Chenghu Zhou
● Distilling Semantic Concept Embeddings from Contrastively Fine-Tuned Language Models
Na Li, Hanane Kteich, Zied Bouraoui, Steven Schockaert
● Distributionally Robust Sequential Recommnedation
Rui Zhou, Xian Wu, Zhaopeng Qiu, Yefeng Zheng, Xu Chen
● DMBIN: A Dual Multi-behavior Interest Network for Click-Through Rate Prediction via Contrastive Learning
Tianqi He, Kaiyuan Li, Shan Chen, Haitao Wang, Qiang Liu, Xingxing Wang, Dong Wang
● Do-GOOD: Towards Distribution Shift Evaluation for Pre-Trained Visual Document Understanding Models
Jiabang He, Yi Hu, Lei Wang, Xing Xu, Ning Liu, Hui Liu, Heng Tao Shen
● DREAM: Adaptive Reinforcement Learning based on Attention Mechanism for Temporal Knowledge Graph Reasoning
Shangfei Zheng, Hongzhi Yin, Tong Chen, Quoc Viet Hung Nguyen, Wei Chen, Lei Zhao
● Dual Contrastive Transformer for Hierarchical Preference Modeling in Sequential Recommendation
Chengkai Huang, Shoujin Wang, Xianzhi Wang, Lina Yao
● Dual Semantic Knowledge Composed Multimodal Dialog Systems
Xiaolin Chen, Xuemeng Song, Yinwei Wei, Liqiang Nie, Tat-Seng Chua
● Dynamic Graph Evolution Learning for Recommendation
Haoran Tang, Shiqing Wu, Guandong Xu, Qing Li
● Dynamic Mixed Membership Stochastic Block Model for Weighted Labeled Networks
Gaël Poux-Médard, Julien Velcin, Sabine Loudcher
● EDIndex: Enabling Fast Data Queries in Edge Storage Systems
Qiang He, Siyu Tan, Feifei Chen, Xiaolong Xu, Lianyong Qi, Xinhong Hei, Hai Jin, Yun Yang
● Editable User Profiles for Controllable Text Recommendations
Sheshera Mysore, Mahmood Jasim, Andrew Mccallum, Hamed Zamani
● EEDN: Enhanced Encoder-Decoder Network with Local and Global Context Learning for POI Recommendation
Xinfeng Wang, Fumiyo Fukumoto, Jin Cui, Yoshimi Suzuki, Jiyi Li, Dongjin Yu
● Ensemble Modeling with Contrastive Knowledge Distillation for Sequential Recommendation
Hanwen Du, Huanhuan Yuan, Pengpeng Zhao, Fuzhen Zhuang, Guanfeng Liu, Lei Zhao, Yanchi Liu, Victor S. Sheng
● ErrorCLR: Semantic Error Classification, Localization and Repair for Introductory Programming Assignments
Siqi Han, Yu Wang, Xuesong Lu
● EulerNet: Adaptive Feature Interaction Learning via Euler’s Formula for CTR Prediction
Zhen Tian, Ting Bai, Wayne Xin Zhao, Ji-Rong Wen, Zhao Cao
● Explainable Conversational Question Answering over Heterogeneous Sources via Iterative Graph Neural Networks
Philipp Christmann, Rishiraj Saha Roy, Gerhard Weikum
● Exploiting Simulated User Feedback for Conversational Search: Ranking, Rewriting, and Beyond
Paul Owoicho, Ivan Sekulic, Mohammad Aliannejadi, Jeffery Dalton, Fabio Crestani
● Exploring scenarios of uncertainty about the users’ preferences in interactive recommendation systems
Nícollas Silva, Thiago Silva, Henrique Hott, Yan Ribeiro, Adriano Pereira, Leonardo Rocha
● Extending Label Aggregation Models with a Gaussian Process to Denoise Crowdsourcing Labels
Dan Li, Maarten de Rijke
● BiTimeBERT: Extending Pre-Trained Language Representations with Bi-Temporal Information
Jiexin Wang, Adam Jatowt, Masatoshi Yoshikawa, Yi Cai
● FiD-Light: Efficient and Effective Retrieval-Augmented Text Generation
Sebastian Hofstätter, Jiecao Chen, Karthik Raman, Hamed Zamani
● Fine-Grained Preference-Aware Personalized Federated POI Recommendation with Data Sparsity
Xiao Zhang, Ziming Ye, Jianfeng Lu, Fuzhen Zhuang, Yanwei Zheng, Dongxiao Yu
● Frequency Enhanced Hybrid Attention Network for Sequential Recommendation
Xinyu Du, Huanhuan Yuan, Pengpeng Zhao, Jianfeng Qu, Fuzhen Zhuang, Guanfeng Liu, Yanchi Liu, Victor S. Sheng
● From Region to Patch: Attribute-Aware Foreground-Background Contrastive Learning for Fine-Grained Fashion Retrieval
Jianfeng Dong, Xiaoman Peng, Zhe Ma, Daizong Liu, Xiaoye Qu, Xun Yang, Jixiang Zhu, Baolong Liu
● Generative-Contrastive Graph Learning for Recommendation
Yonghui Yang, Zhengwei Wu, Le Wu, Kun Zhang, Richang Hong, Zhiqiang Zhang, Jun Zhou, Meng Wang
● Graph Masked Autoencoder for Sequential Recommendation
Yaowen Ye, Lianghao Xia, Chao Huang
● HDNR: A Hyperbolic-Based Debiased Approach for Personalized News Recommendation
Shicheng Wang, Shu Guo, Lihong Wang, Tingwen Liu, Hongbo Xu
● Hear Me Out: A Study on the Use of the Voice Modality for Crowdsourced Relevance Assessments
Nirmal Roy, Agathe Balayn, David Maxwell, Claudia Hauff
● Unsupervised Readability Assessment via Learning from Weak Readability Signals
Yuliang Liu, Zhiwei Jiang, Yafeng Yin, Cong Wang, Sheng Chen, Zhaoling Chen, Qing Gu
● Hydrus: Improving Personalized Quality of Experience in Short-form Video Services
Zhiyu Yuan, Kai Ren, Gang Wang, Xin Miao
● 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, Zhaochun Ren
● BeamQA: Multi-hop Knowledge Graph Question Answering with Sequence-to-Sequence Prediction and Beam Search
Farah Atif, Ola El Khatib, Djellel Difallah
● InceptionXML: A Lightweight Framework with Synchronized Negative Sampling for Short Text Extreme Classification
Siddhant Kharbanda, Atmadeep Banerjee, Devaansh Gupta, Akash Palrecha, Rohit Babbar
● Incorporating Structured Sentences with Time-enhanced BERT for Fully-inductive Temporal Relation Prediction
Zhongwu Chen, Chengjin Xu, Fenglong Su, Zhen Huang, Yong Dou
● AutoTransfer: Instance Transfer for Cross-Domain Recommendations
Jingtong Gao, Xiangyu Zhao, Bo Chen, Fan Yan, Huifeng Guo, Ruiming Tang
● Intent-aware Ranking Ensemble for Personalized Recommendation
Jiayu Li, Peijie Sun, Zhefan Wang, Weizhi Ma, Yangkun Li, Min Zhang, Zhoutian Feng, Daiyue Xue
● Can ChatGPT Write a Good Boolean Query for Systematic Review Literature Search?
Shuai Wang, Harrisen Scells, Bevan Koopman, Guido Zuccon
● It’s Enough: Relaxing Diagonal Constraints in Linear Autoencoders for Recommendation
Jaewan Moon, Hye-young Kim, Jongwuk Lee
● Keyword-Based Diverse Image Retrieval by Semantics-aware Contrastive Learning and Transformer
Minyi Zhao, Jinpeng Wang, Dongliang Liao, Yiru Wang, Huanzhong Duan, Shuigeng Zhou
● Knowledge-enhanced Multi-View Graph Neural Networks for Session-based Recommendation
Qian Chen, Zhiqiang Guo, Jianjun Li, Guohui Li
● Knowledge-refined Denoising Network for Robust Recommendation
Xinjun Zhu, Yuntao Du, Yuren Mao, Lu Chen, Yujia Hu, Yunjun Gao
● Large Language Models are Versatile Decomposers: Decomposing Evidence and Questions for Table-based Reasoning
Yunhu Ye, Binyuan Hui, Min Yang, Binhua Li, Fei Huang, Yongbin Li
● Law Article-Enhanced Legal Case Matching: A Causal Learning Approach
Zhongxiang Sun, Jun Xu, Xiao Zhang, Zhenhua Dong, Ji-Rong Wen
● Leader-Generator Net: Dividing Skill and Implicitness for Conquering FairytaleQA
Wei Peng, Wanshui Li, Yue Hu
● Learn from Relational Correlations and Periodic Events for Temporal Knowledge Graph Reasoning
Ke Liang, Lingyuan Meng, Meng Liu, Yue Liu, Wenxuan Tu, Siwei Wang, Sihang Zhou, Xinwang Liu
● Learnable Pillar-based Re-ranking for Image-Text Retrieval
Leigang Qu, Meng Liu, Wenjie Wang, Zhedong Zheng, Liqiang Nie, Tat-Seng Chua
● Learning Fine-grained User Interests for Micro-video Recommendation
Yu Shang, Chen Gao, Jiansheng Chen, Depeng Jin, Meng Wang, Yong Li
● Learning to Re-rank with Constrained Meta-Optimal Transport
Andrés Hoyos-Idrobo
● Lexically-Accelerated Dense Retrieval
Hrishikesh Kulkarni, Sean Macavaney, Nazli Goharian, Ophir Frieder
● LightGT: A Light Graph Transformer for Multimedia Recommendation
Yinwei Wei, Wenqi Liu, Fan Liu, Xiang Wang, Liqiang Nie, Tat-Seng Chua
● LinRec: Linear Attention Mechanism for Long-term Sequential Recommender Systems
Langming Liu, Liu Cai, Chi Zhang, Xiangyu Zhao, Jingtong Gao, Wanyu Wang, Yifu Lv, Wenqi Fan, Yiqi Wang, Ming He, Zitao Liu, Qing Li
● LOAM: Improving Long-tail Session-based Recommendation via Niche Walk Augmentation and Tail Session Mixup
Heeyoon Yang, YunSeok Choi, Gahyung Kim, Jee-Hyong Lee
● M2EU: Meta Learning for Cold-start Recommendation via Enhancing User Preference Estimation
Zhenchao Wu, Xiao Zhou
● 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, Wei Wu
● MAMO: Fine-Grained Vision-Language Representations Learning with Masked Multimodal Modeling
Zijia Zhao, Longteng Guo, Xingjian He, Shuai Shao, Zehuan Yuan, Jing Liu
● Manipulating Federated Recommender Systems: Poisoning with Synthetic Users and Its Countermeasures
Wei Yuan, Quoc Viet Hung Nguyen, Tieke He, Liang Chen, Hongzhi Yin
● Graph Transformer for Recommendation
Chaoliu Li, Lianghao Xia, Xubin Ren, Yaowen Ye, Yong Xu, Chao Huang
● Measuring Item Global Residual Value for Fair Recommendation
Jiayin Wang, Weizhi Ma, Chumeng Jiang, Min Zhang, Yuan Zhang, Biao Li, Peng Jiang
● MELT: Mutual Enhancement of Long-Tailed User and Item for Sequential Recommendation
Kibum Kim, Dongmin Hyun, Sukwon Yun, Chanyoung Park
● MEME:Multi-Encoder Multi-Expert Framework with Data Augmentation for Video Retrieval
Seong-Min Kang, Yoon-Sik Cho
● Meta-optimized Contrastive Learning for Sequential Recommendation
Xiuyuan Qin, Huanhuan Yuan, Pengpeng Zhao, Junhua Fang, Fuzhen Zhuang, Guanfeng Liu, Yanchi Liu, Victor Sheng
● MGeo: Multi-Modal Geographic Language Model Pre-Training
Ruixue Ding, Boli Chen, Pengjun Xie, Fei Huang, Xin Li, Qiang Zhang, Yao Xu
● Mining Stable Preferences: Adaptive Modality Decorrelation for Multimedia Recommendation
Jinghao Zhang, Qiang Liu, Shu Wu, Liang Wang
● Mixed-Curvature Manifolds Interaction Learning for Knowledge Graph-aware Recommendation
Jihu Wang, Yuliang Shi, Han Yu, Xinjun Wang, Zhongmin Yan, Fanyu Kong
● ML-LJP: Multi-Law Aware Legal Judgment Prediction
Yifei Liu, Yiquan Wu, Yating Zhang, Changlong Sun, Weiming Lu, Fei Wu, Kun Kuang
● Aligning Distillation For Cold-start Item Recommendation
Feiran Huang, Zefan Wang, Xiao Huang, Yufeng Qian, Zhetao Li, Hao Chen
● Model-Agnostic Decentralized Collaborative Learning for On-Device POI Recommendation
Jing Long, Tong Chen, Quoc Viet Hung Nguyen, Guandong Xu, Kai Zheng, Hongzhi Yin
● Multi-behavior Self-supervised Learning for Recommendation
Jingcao Xu, Chaokun Wang, Cheng Wu, Yang Song, Kai Zheng, Xiaowei Wang, Changping Wang, Guorui Zhou, Kun Gai
● Multi-order Matched Neighborhood Consistent Graph Alignment in a Union Vector Space
Wei Tang, Haifeng Sun, Jingyu Wang, Qi Qi, Jing Wang, Hao Yang, Shimin Tao
● Multi-Scenario Ranking with Adaptive Feature Learning
Yu Tian, Bofang Li, Si Chen, Xubin Li, Hongbo Deng, Jian Xu, Bo Zheng, Qian Wang, Chenliang Li
● Multi-view Hypergraph Contrastive Policy Learning for Conversational Recommendation
Sen Zhao, Wei Wei, Xian-Ling Mao, Shuai Zhu, Minghui Yang, Zujie Wen, Dangyang Chen, Feida Zhu
● Multi-View Multi-Aspect Neural Networks for Next-Basket Recommendation
Zhiying Deng, Jianjun Li, Zhiqiang Guo, Wei Liu, Li Zou, Guohui Li
● Multimodal Counterfactual Learning Network for Multimedia-based Recommendation
Shuaiyang Li, Dan Guo, Kang Liu, Richang Hong, Feng Xue
● Multivariate Representation Learning for Information Retrieval
Hamed Zamani, Michael Bendersky
● News Popularity Beyond the Click-Through-Rate for Personalized Recommendations
Ashutosh Nayak, Mayur Garg, Rajasekhara Reddy Duvvuru Muni
● Next Basket Recommendation with Intent-aware Hypergraph Adversarial Network
Ran Li, Liang Zhang, Guannan Liu, Junjie Wu
● Normalizing Flow-based Neural Process for Few-Shot Knowledge Graph Completion
Linhao Luo, Reza Haffari, Yuan Fang Li, Shirui Pan
● Not Just Skipping: Understanding the Effect of Sponsored Content on Users’ Decision-Making in Online Health Search
Anat Hashavit, Hongning Wang, Tamar Stern, Sarit Kraus
● On the Impact of Outlier Bias on User Clicks
Fatemeh Sarvi, Ali Vardasbi, Mohammad Aliannejadi, Sebastian Schelter, Maarten De Rijke
● One Blade for One Purpose: Advancing Math Information Retrieval using Hybrid Search
Wei Zhong, Sheng-Chieh Lin, Jheng-Hong Yang, Jimmy Lin
● Online Conversion Rate Prediction via Neural Satellite Networks in Delayed Feedback Advertising
Qiming Liu, Haoming Li, Xiang Ao, Yuyao Guo, Zhihong Dong, Ruobing Zhang, Qiong Chen, Jianfeng Tong, Qing He
● Personalized Federated Relation Classification over Heterogeneous Texts
Ning Pang, Xiang Zhao, Weixin Zeng, Ji Wang, Weidong Xiao
● Personalized Retrieval over Millions of Items
Hemanth Vemuri, Sheshansh Agrawal, Shivam Mittal, Deepak Saini, Akshay Soni, Abhinav V. Sambasivan, Wenhao Lu, Yajun Wang, Mehul Parsana, Purushottam Kar, Manik Varma
● PLATE: A Prompt-Enhanced Paradigm for Multi-Scenario Recommendations
Yuhao Wang, Xiangyu Zhao, Bo Chen, Qidong Liu, Huifeng Guo, Huanshuo Liu, Yichao Wang, Rui Zhang, Ruiming Tang
● Poisoning Self-supervised Learning Based Sequential Recommendations
Yanling Wang, Yuchen Liu, Qian Wang, Cong Wang, Chenliang Li
● Prompt Learning for News Recommendation
Zizhuo Zhang, Bang Wang
● RCENR: A Reinforced and Contrastive Heterogeneous Network Reasoning Model for Explainable News Recommendation
Hao Jiang, Chuanzhen Li, Juanjuan Cai, Jingling Wang
● Rectifying Unfairness in Recommendation Feedback Loop
Mengyue Yang, Jun Wang, Jean-Francois Ton
● Reformulating CTR Prediction: Learning Invariant Feature Interactions for Recommendation
Yang Zhang, Tianhao Shi, Fuli Feng, Wenjie Wang, Dingxian Wang, Xiangnan He, Yongdong Zhang
● Relation-Aware Multi-Positive Contrastive Knowledge Graph Completion with Embedding Dimension Scaling
Bin Shang, Yinliang Zhao, Di Wang, Jun Liu
● Representation and Labeling Gap Bridging for Cross-lingual Named Entity Recognition
Xinghua Zhang, Bowen Yu, Jiangxia Cao, Quangang Li, Xuebin Wang, Tingwen Liu, Hongbo Xu
● Rethinking Benchmarks for Cross-modal Image-text Retrieval
Weijing Chen, Linli Yao, Qin Jin
● RHB-Net: A Relation-aware Historical Bridging Network for Text2SQL Auto-Completion
Bolong Zheng, Lei Bi, Ruijie Xi, Lu Chen, Yunjun Gao, Xiaofang Zhou, Christian Jensen
● Safe Deployment for Counterfactual Learning to Rank with Exposure-Based Risk Minimization
Shashank Gupta, Harrie Oosterhuis, Maarten de Rijke
● SAILER: Structure-aware Pre-trained Language Model for Legal Case Retrieval
Haitao Li, Qingyao Ai, Jia Chen, Qian Dong, Yueyue Wu, Yiqun Liu, Chong Chen, Qi Tian
● SCHash: Speedy Simplicial Complex Neural Networks via Randomized Hashing
Xuan Tan, Wei Wu, Chuan Luo
● Schema-aware Reference as Prompt Improves Data-Efficient Knowledge Graph Construction
Yunzhi Yao, Shengyu Mao, Ningyu Zhang, Xiang Chen, Shumin Deng, Xi Chen, Huajun Chen
● SciMine: An Efficient Systematic Prioritization Model Based on Richer Semantic Information
Fang Guo, Yun Luo, Linyi Yang, Yue Zhang
● Seq-HGNN: Learning Sequential Node Representation on Heterogeneous Graph
Chenguang Du, Kaichun Yao, Hengshu Zhu, Deqing Wang, Fuzhen Zhuang, Hui Xiong
● Session Search with Pre-trained Graph Classification Model
Shengjie Ma, Chong Chen, Jiaxin Mao, Qi Tian, Xuhui Jiang
● Single-shot Feature Selection for Multi-task Recommendations
Yejing Wang, Zhaocheng Du, Xiangyu Zhao, Bo Chen, Huifeng Guo, Ruiming Tang, Zhenhua Dong
● Smooth Operators for Effective Systematic Review Queries
Harrisen Scells, Ferdinand Schlatt, Martin Potthast
● Soft Prompt Decoding for Multilingual Dense Retrieval
Zhiqi Huang, Hansi Zeng, Hamed Zamani, James Allan
● Spatio-Temporal Hypergraph Learning for Next POI Recommendation
Xiaodong Yan, Tengwei Song, Yifeng Jiao, Jianshan He, Jiaotuan Wang, Ruopeng Li, Wei Chu
● Strategy-aware Bundle Recommender System
Yinwei Wei, Xiaohao Liu, Yunshan Ma, Xiang Wang, Liqiang Nie, Tat-Seng Chua
● StreamE: Learning to Update Representations for Temporal Knowledge Graphs in Streaming Scenarios
Jiasheng Zhang, Jie Shao, Bin Cui
● Subgraph Search over Neural-Symbolic Graphs
Ye Yuan, Delong Ma, Anbiao Wu, Jianbin Qin
● Leveraging Transferable Knowledge Concept Graph Embedding for Cold-Start Cognitive Diagnosis
Weibo Gao, Hao Wang, Qi Liu, Fei Wang, Xin Lin, Linan Yue, Zheng Zhang, Rui Lv, Shijin Wang
● 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, Enhong Chen
● Topic-enhanced Graph Neural Networks for Extraction-based Explainable Recommendation
Jie Shuai, Le Wu, Kun Zhang, Peijie Sun, Richang Hong, Meng Wang
● Topic-oriented Adversarial Attacks against Black-box Neural Ranking Models
Yu-An Liu, Ruqing Zhang, Jiafeng Guo, Maarten De Rijke, Wei Chen, Yixing Fan, Xueqi Cheng
● Towards Multi-Interest Pre-training with Sparse Capsule Network
Zuoli Tang, Lin Wang, Lixin Zou, Xiaolu Zhang, Jun Zhou, Chenliang Li
● Triple Structural Information Modelling for Accurate, Explainable and Interactive Recommendation
Jiahao Liu, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Li Shang, Ning Gu
● Uncertainty Quantification for Extreme Classification
Jyun-Yu Jiang, Wei-Cheng Chang, Jiong Zhang, Cho-Jui Hsieh, Hsiang-Fu Yu
● Understand the Dynamic World: An End-to-End Knowledge Informed Framework for Open Domain Entity State Tracking
Mingchen Li, Lifu Huang
● Unsupervised Story Discovery from Continuous News Streams via Scalable Thematic Embedding
Susik Yoon, Dongha Lee, Yunyi Zhang, Jiawei Han
● Using Code Generation To Answer Simulation Questions in Chemistry Texts
Gal Peretz, Mousa Arraf, Kira Radinsky
● Weighted Knowledge Graph Embedding
Zhao Zhang, Zhanpeng Guan, Fuwei Zhang, Fuzhen Zhuang, Zhulin An, Fei Wang, Yongjun Xu
● When Newer is Not Better: Does Deep Learning Really Benefit Recommendation From Implicit Feedback?
Yushun Dong, Jundong Li, Tobias Schnabel
● When Search Meets Recommendation: Learning Disentangled Search Representation for Recommendation
Zihua Si, Zhongxiang Sun, Xiao Zhang, Jun Xu, Xiaoxue Zang, Yang Song, Kun Gai, Ji-Rong Wen
● Wisdom of Crowds and Fine-Grained Learning for Serendipity Recommendations
Zhe Fu, Xi Niu, Li Yu