3.按照研究话题划分
3.1 Bias/Debias in Recommender System
- Interpolative Distillation for Unifying Biased and Debiased Recommendation
- Co-training Disentangled Domain Adaptation Network for Leveraging Popularity Bias in Recommenders 【训练解耦的域适应网络来利用流行度偏差】
- Bilateral Self-unbiased Recommender Learning from Biased Implicit Feedback 【双边去偏】
- Mitigating Consumer Biases in Recommendations with Adversarial Training 【short paper，对抗训练去偏】
- Neutralizing Popularity Bias in Recommendation Models 【short paper，中和流行度偏差】
- DeSCoVeR: Debiased Semantic Context Prior for Venue Recommendation 【short paper，在场所推荐中去除语义上下文先验】
3.2 Explanation in Recommender System
- Post Processing Recommender Systems with Knowledge Graphs for Recency, Popularity, and Diversity of Explanations 【使用知识图谱为推荐生成崭新的、多样的解释】
- PEVAE: A hierarchical VAE for personalized explainable recommendation. 【利用层次化VAE进行个性化可解释推荐】
- Explainable Session-based Recommendation with Meta-Path Guided Instances and Self-Attention Mechanism 【short paper， 基于元路径指导和自注意力机制的可解释会话推荐】
3.3 Long-tail/Cold-start in Recommender System
- Socially-aware Dual Contrastive Learning for Cold-Start Recommendation 【short paper，社交感知的双重对比学习】
- Transform Cold-Start Users into Warm via Fused Behaviors in Large-Scale Recommendation 【short paper，通过融合行为转换冷启动用户】
- Generative Adversarial Framework for Cold-Start Item Recommendation 【short paper，针对冷启动商品的生成对抗框架】
- Improving Item Cold-start Recommendation via Model-agnostic Conditional Variational Autoencoder 【short paper，模型无关的自编码器提升商品冷启动推荐】
3.4 Fairness in Recommender System
- Joint Multisided Exposure Fairness for Recommendation 【综合考虑多边的曝光公平性】
- ProFairRec: Provider Fairness-aware News Recommendation 【商家公平的新闻推荐】
- CPFair: Personalized Consumer and Producer Fairness Re-ranking for Recommender Systems 【用户和商家公平的重排序】
- Explainable Fairness for Feature-aware Recommender Systems 【考虑特征的推荐系统中的可解释公平】
- Selective Fairness in Recommendation via Prompts 【short paper，通过提示保证可选的公平性】
- Regulating Provider Groups Exposure in Recommendations 【short paper，调整商家组曝光】
3.5 Diversity in Recommender System
- DAWAR: Diversity-aware Web APIs Recommendation for Mashup Creation based on Correlation Graph 【多样化Web API推荐】
- Mitigating the Filter Bubble while Maintaining Relevance: Targeted Diversification with VAE-based Recommender Systems 【short paper，定向多样化】
- Diversity vs Relevance: a practical multi-objective study in luxury fashion recommendations 【short paper，奢侈品推荐中的多目标研究】
3.6 Attack/Denoise in Recommender System
- Learning to Denoise Unreliable Interactions for Graph Collaborative Filtering 【数据去噪】
- Less is More: Reweighting Important Spectral Graph Features for Recommendation 【评估重要的图谱特征】
- Denoising Time Cycle Modeling for Recommendation 【short paper，去噪时间循环建模】
- Adversarial Graph Perturbations for Recommendations at Scale 【short paper，大规模推荐中的对抗图扰动】
3.7Others
- Privacy-Preserving Synthetic Data Generation for Recommendation 【隐私保护的仿真数据生成】
- User-Aware Multi-Interest Learning for Candidate Matching in Recommenders 【使用用户多兴趣学习进行候选匹配】
- User-controllable Recommendation Against Filter Bubbles 【用户可控的推荐】
- Rethinking Correlation-based Item-Item Similarities for Recommender Systems 【short paper，反思基于关系的商品相似度】
- ReLoop: A Self-Correction Learning Loop for Recommender Systems 【short paper，推荐系统中的自修正循环学习】
- Towards Results-level Proportionality for Multi-objective Recommender Systems 【short paper，结果均衡的多目标推荐系统】
4.其他研究方向
4.1 QA
DGQAN: Dual Graph Question-Answer Attention Networks for Answer Selection 【双图注意力网络】
- Counterfactual Learning To Rank for Utility-Maximizing Query Autocompletion 【反事实学习】
- PTAU: Prompt Tuning for Attributing Unanswerable Questions 【提示微调】
- Conversational Question Answering on Heterogeneous Sources 【异质来源的问答】
- A Non-Factoid Question-Answering Taxonomy
- QUASER: Question Answering with Scalable Extractive Rationalization
- Detecting Frozen Phrases in Open-Domain Question Answering 【short paper 在开放域问答中检测固定短语】
- Answering Count Query with Explanatory Evidence 【short paper】
4.1 Knowledge Graph
- Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completion 【多模态知识图谱补全】
- Incorporating Context Graph with Logical Reasoning for Inductive Relation Prediction 【合并上下文图和逻辑推理进行归纳式关系预测】
- Meta-Knowledge Transfer for Inductive Knowledge Graph Embedding【元知识迁移解决归纳式知识图谱嵌入】
- Re-thinking Knowledge Graph Completion Evaluation from an Information Retrieval Perspective 【从信息检索视角思考知识图谱补全的评测】
- Relation-Guided Few-Shot Relational Triple Extraction 【short paper，关系指导的few-shot三元组抽取】
4.2 Conversation/ Dialog
- Unified Dialog Model Pre-training for Task-Oriented Dialog Understanding and Generation 【统一对话理解和生成的预训练模型】
- Interacting with Non-Cooperative User: A New Paradigm for Proactive Dialogue Policy 【主动对话策略的新范式】
- COSPLAY: Concept Set Guided Personalized Dialogue System 【概念集合指导的个性化对话系统】
- Understanding User Satisfaction with Task-Oriented Dialogue Systems 【理解用户满意度】
- A Multi-Task Based Neural Model to Simulate Users in Goal Oriented Dialogue Systems 【short paper 多任务模型仿真用户】
- Task-Oriented Dialogue System as Natural Language Generation 【short paper，自然语言生成的对话系统】
4.3 Summarization
- HTKG: Deep Keyphrase Generation with Neural Hierarchical Topic Guidance
- V2P: Vision-to-Prompt based Multi-Modal Product Summary Generation
- Unifying Cross-lingual Summarization and Machine Translation with Compression Rate 【使用压缩率统一跨语言总结和机器翻译】
- ADPL: Adversarial Prompt-based Domain Adaptation for Dialogue Summarization with Knowledge Disentanglement 【基于提示的对抗领域自适应】
- Summarizing Legal Regulatory Documents using Transformers 【short ，使用Transformers总结法律监管文档】
- QSG Transformer: Transformer with Query-Attentive Semantic Graph for Query-Focused Summarization 【short paper】
- MuchSUM: Multi-channel Graph Neural Network for Extractive Summarization 【short paper，多通道图神经网络】
- Lightweight Meta-Learning for Low-Resource Abstractive Summarization 【short paper， 轻量级元学习】
- Extractive Elementary Discourse Units for Improving Abstractive Summarization 【short paper】
4.4 Multi-Modality
Tag-assisted Multimodal Sentiment Analysis under Uncertain Missing Modalities
- Progressive Learning for Image Retrieval with Hybrid-Modality Queries
- CenterCLIP: Token Clustering for Efficient Text-Video Retrieval
- Multimodal Entity Linking with Gated Hierarchical Fusion and Contrastive Training
- CRET: Cross-Modal Retrieval Transformer for Efficient Text-Video Retrieval
- Bit-aware Semantic Transformer Hashing for Multi-modal Retrieval
- Video Moment Retrieval from Text Queries via Single Frame Annotation
- Multimodal Disentanglement Variational AutoEncoders for Zero-Shot Cross-Modal Retrieval
- A Multitask Framework for Sentiment, Emotion and Sarcasm aware Cyberbullying Detection in Multi-modal Code-Mixed Memes
- Animating Images to transfer CLIP for Video-Text Retrieval 【short paper， 使用CLIP进行视频-文本检索】
- Image-Text Retrieval via Contrastive Learning with Auxiliary Generative Features and Support-set Regularization 【short paper】
- An Efficient Fusion Mechanism for Multimodal Low-resource Setting 【short paper，在低资源下的一种高效融合机制】
4.5 Generation
- Mutual Disentanglement Learning for Joint Fine-Grained Sentiment Classification and Controllable Text Generation
- Target-aware Abstractive Related Work Generation with Contrastive Learning 【利用对比学习生成生成相关工作】
- Generating Clarifying Questions with Web Search Results 【利用Web搜索结果生成清晰问题】
- Choosing The Right Teammate For Cooperative Text Generation 【short paper 】
4.6 Representation Learning
- Structure and Semantics Preserving Document Representations 【保留结构和语义的文档表示】
- Unsupervised Belief Representation Learning with Information-Theoretic Variational Graph Auto-Encoders
