第33届CIKM会议将于2024年10月21日至25日在美国爱达荷州博伊西举行。CIKM会议是数据库／数据挖掘／内容检索领域顶级国际会议，也是中国计算机学会规定的CCF B类会议。关于该会议在历年推荐系统论文收录情况请参考下文：
CIKM2023推荐系统论文整理
CIKM2022推荐系统论文集锦
本文主要是从Full Papers和Short Papers中筛选出与推荐系统有关的论文供大家学习，其中长文63篇，短文21篇。其中大部分论文都已上传到Arxiv，大家可以自行下载进行阅读，也可以前往每周的论文周报进行查看。
Full Papers
本会议所接收的长文主要是关注对经典协同过滤方法的改造、序列推荐、脑电图推荐、多模态推荐、扩散推荐等等。
fp0053 Natural Language-Assisted Multi-modal
Medication Recommendationfp0072 Sparks of Surprise: Multi-objective
Recommendations with Hierarchical Decision Transformers for Diversity, Novelty,
and Serendipityfp0082 Collaborative Alignment for Recommendationfp0137 CausalMed: Causality-Based Personalized
Medication Recommendation Centered on Patient Health Statefp0161 MultiLoRA: Multi-Directional Low Rank
Adaptation for Multi-Domain Recommendationfp0176 A Power Method to Alleviate Over-smoothing
for Recommendationfp0209 Large Language Models Enhanced Collaborative
Filteringfp0240 Quantum Cognition-Inspired EEG-based
Recommendation via Graph Neural Networksfp0270 Learnable Item Tokenization for Generative
Recommendationfp0287 Hyperbolic Contrastive Learning for
Cross-Domain Recommendationfp0358 Multi-modal Food Recommendation with
Health-aware Knowledge Distillationfp0417 Adversarial Text Rewriting for Text-aware
Recommender Systemsfp0425 The Devil is in the Sources! Knowledge
Enhanced Cross-Domain Recommendation in an Information Bottleneck Perspectivefp0449 Collaborative Cross-modal Fusion with Large
Language Model for Recommendationfp0455 Social Influence Learning for Recommendation
Systemsfp0458 MemoCRS: Memory-enhanced Sequential
Conversational Recommender Systems with Large Language Modelsfp0518 A Universal Sets-level Optimization
Framework for Next Set Recommendationfp0525 Aligning Large Language Model with Direct
Multi-Preference Optimization for Recommendationfp0536 HierRec: Scenario-Aware Hierarchical
Modeling for Multi-scenario Recommendationsfp0542 Watermarking Recommender Systemsfp0547 GUME: Graphs and User Modalities Enhancement
for Long-Tail Multimodal Recommendationfp0551 Multi-Task Recommendation with Task
Information Decouplingfp0576 AlignRec: Aligning and Training in
Multimodal Recommendationsfp0594 On Evaluation Metrics for Diversity-enhanced
Recommendationsfp0597 RecDiff: Diffusion Model for Social Recommendationfp0609 ROLeR: Effective Reward Shaping in Offline
Reinforcement Learning for Recommender Systemsfp0628 Decoupled Behavior-based Contrastive
Recommendationfp0642 A General Strategy Graph Collaborative
Filtering for Recommendation Unlearningfp0645 Scalable Dynamic Embedding Size Search for
Streaming Recommendationfp0674 SAQRec: Aligning Recommender Systems to User
Satisfaction via Questionnaire Feedbackfp0688 Spectral and Geometric Spaces Representation
Regularization for Multi-Modal Sequential Recommendationfp0729 Context Matters: Enhancing Sequential
Recommendation with Context-aware Diffusion-based Contrastive Learningfp0730 LAMRec: Label-aware Multi-view Drug
Recommendationfp0793 Aligning Explanations for Recommendation
with Rating and Feature via Maximizing Mutual Informationfp0854 On Causally Disentangled State
Representation Learning for Reinforcement Learning based Recommender Systemsfp0921 Relative Contrastive Learning for Sequential
Recommendation with Similarity-based Positive Sample Selectionfp0928 Efficient and Robust Regularized Federated
Recommendationfp0973 UniRec: A Dual Enhancement of Uniformity and
Frequency in Sequential Recommendationsfp0979 MMLRec: A Unified Multi-Task and
Multi-Scenario Learning Benchmark for Recommendationfp0987 Content-Based Collaborative Generation for
Recommender Systemsfp1001 AlignGroup: Learning and Aligning Group
Consensus with Member Preferences for Group Recommendationfp1034 HGCH: A Hyperbolic Graph Convolution Network
Model for Heterogeneous Collaborative Graph Recommendationfp1084 MuLe: Multi-Grained Graph Learning for
Multi-Behavior Recommendationfp1152 Behavior-Dependent Linear Recurrent Units for
Efficient Sequential Recommendationfp1154 PTSR: Prefix-Target Graph-based Sequential
Recommendationfp1196 Calibration-Disentangled Learning and
Relevance-Prioritized Reranking for Calibrated Sequential Recommendationfp1211 Multi-Behavior Generative Recommendationfp1313 LLM4MSR: An LLM-Enhanced Paradigm for
Multi-Scenario Recommendationfp1375 Bridging User Dynamics: Transforming
Sequential Recommendations with Schrödinger Bridge and Diffusion Modelsfp1439 Mitigating Exposure Bias in Online Learning
to Rank Recommendation: A Novel Reward Model for Cascading Banditsfp1521 Do We Really Need Graph Convolution During
Training? Light Post-Training Graph-ODE for Efficient Recommendationfp1534 Preference Prototype-Aware Learning for
Universal Cross-Domain Recommendationfp1594 DIIT: A Domain-Invariant Information
Transfer Method for Industrial Cross-Domain Recommendationfp1656 ELCoRec: Enhance Language Understanding with
Co-Propagation of Numerical and Categorical Features for Recommendationfp1678 Reformulating Conversational Recommender
Systems as Tri-Phase Offline Policy Learningfp1783 PACIFIC: Enhancing Sequential Recommendation
via Preference-aware Causal Intervention and Counterfactual Data Augmentationfp1795 Interaction-level Membership Inference
Attack against Recommender Systems with Long-tailed Distributionfp1823 CHDAER:Consistent Hashing-based Data
Allocation for Efficient Recommendation in Edge Environmentfp1890 EFVAE: Efficient Federated Variational
Autoencoder for Collaborative Filteringfp2060 Attacking Visually-aware Recommender Systems
with Transferable and Imperceptible Adversarial Stylesfp2111 Contrastive Learning on Medical Intents for
Sequential Prescription Recommendationfp2183 Retrieval-Oriented Knowledge for
Click-Through Rate Predictionfp2289 Enhancing Click-through Rate Prediction in
Recommendation Domain with Search Query Representation
Short Papers
本次会议接受的短文主要包括序列推荐、多模态推荐、CTR预测、大语言模型推荐等多方面的工作，分别从知识图高阶结构、对比学习、增量学习、知识蒸馏等多个方面对推荐模型进行了研究，具体信息如下。
sp2535 Learning the Dynamics in Sequential
Recommendation by Exploiting Real-time Informationsp2536 Do We Really Need to Drop Items with Missing
Modalities in Multimodal Recommendation?sp2573 PP4RNR: Popularity- and Position-Aware
Contrastive Learning for Retrieval-Driven News Recommendationsp2594 STAR: Sparse Text Approach for
Recommendationsp2597 Enhancing Content-based Recommendation via
Large Language Modelsp2608 Enhancing CTR Prediction through Sequential
Recommendation Pre-training: Introducing the SRP4CTR frameworksp2612 Improved Estimation of Ranks for Learning
Item Recommenders with Negative Samplingsp2636 Post-Training Embedding Enhancement for
Long-Tail Recommendationsp2726 Contrastive Disentangled Representation
Learning for Debiasing Recommendation with Uniform Datasp2762 Dual-level Intents Modeling for
Knowledge-aware Recommendationsp2764 Towards Better Utilization of Multiple Views
for Bundle Recommendationsp2766 Exploring High-Order User Preference with
Knowledge Graph for Recommendationsp2776 Improving Prompt-based News Recommendation
with Individual Template and Customized Answersp2786 Preliminary Study on Incremental Learning
for Large Language Model-based Recommender Systemssp2870 Exploiting Preferences in Loss Functions for
Sequential Recommendation via Weak Transitivitysp2886 MARS: Matching Attribute-aware
Representations for Text-based Sequential Recommendationsp2911 Momentum Contrastive Bidirectional Encoding
with Self-Distillation for Sequential Recommendationsp2913 Knowledge-enhanced Dynamic Modeling
framework for Multi-Behavior Recommendationsp3019 RecPrompt: A Self-tuning Prompting Framework
for News Recommendation Using Large Language Modelssp3233 Ask or Recommend: An Empirical Study on
Conversational Product Searchsp3268 RECE: Reduced Cross-Entropy Loss for
Large-Catalogue Sequential Recommenders推荐阅读
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