Conference Paper
Table of contents
SIGIR, Recsys, WSDM, KDD, etc.
None means unavailable URL or papers that have not been published yet.
- 2023
- 2022
2023
WSDM 2023
- Search Behavior Prediction: A Hypergraph Perspective
- CL4CTR: A Contrastive Learning Framework for CTR Prediction
- IDNP: Interest Dynamics Modeling using Generative Neural Processes for Sequential Recommendation
None:Learning to Distinguish Multi-User Coupling Behaviors for TV RecommendationNone:Towards Universal Cross-Domain Recommendation- One for All, All for One: Learning and Transferring User Embeddings for Cross-Domain Recommendation
None:Slate-Aware Ranking for Recommendation- Directed Acyclic Graph Factorization Machines for CTR Prediction via Knowledge Distillation
- Knowledge Enhancement for Contrastive Multi-Behavior Recommendation
- Disentangled Representation for Diversified Recommendations
- Heterogeneous Graph-based Context-aware Document Ranking
- Cognition-aware Knowledge Graph Reasoning for Explainable Recommendation
None:Separating Examination and Trust Bias from Click Predictions for Unbiased Relevance RankingNone:Self-Supervised Group Graph Collaborative Filtering for Group Recommendation- Learning Topical Stance Embeddings from Signed Social Graphs
None:Calibrated Recommendations as a Maximum Flow Problem- Search Behavior Prediction: A Hypergraph Perspective
- DisenPOI: Disentangling Sequential and Geographical Influence for Point-of-Interest Recommendation
None:Multi-Intentions Oriented Contrastive Learning for Sequential Recommendation- MUSENET: Multi-Scenario Learning for Repeat-Aware Personalized Recommendation
None:A Personalized Neighborhood-based Model for Within-basket Recommendation in Grocery ShoppingNone:Disentangled Negative Sampling for Collaborative Filtering- DIGMN: Dynamic Intent Guided Meta Network for Differentiated User Engagement Forecasting in Online Professional Social Platforms
None:SGCCL: Siamese Graph Contrastive Consensus Learning for Personalized RecommendationNone:Multimodal Pre-Training with Self-Distillation for Product Understanding in E-CommerceNone:Relation Preference oriented High-order Sampling for Recommendation- Variational Reasoning over Incomplete Knowledge Graphs for Conversational Recommendation
None:Exploiting Explicit and Implicit Item relationships for Session-based Recommendation- Meta Policy Learning for Cold-Start Conversational Recommendation
- Efficiently Leveraging Multi-level User Intent for Session-based Recommendation via Atten-Mixer Network
- Simplifying Graph-based Collaborative Filtering for Recommendation
None:AutoGen: An Automated Dynamic Model Generation Framework for Recommender SystemNone:A Causal View for Item-level Effect of Recommendation on User Preference- Federated Unlearning for On-Device Recommendation
- Explicit Counterfactual Data Augmentation for Recommendation
None:Uncertainty Quantification for Fairness in Two-Stage Recommender Systems- Generating Explainable Product Comparisons for Online Shopping
- Unbiased Knowledge Distillation for Recommendation
- VRKG4Rec: Virtual Relational Knowledge Graph for Recommendation
None:Knowledge-Adaptive Contrastive Learning for RecommendationNoneHeterogeneous Graph Contrastive Learning for Recommendation
ICLR 2023
- Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems
- ResAct: Reinforcing Long-term Engagement in Sequential Recommendation with Residual Actor
- Personalized Reward Learning with Interaction-Grounded Learning (IGL)
- TDR-CL: Targeted Doubly Robust Collaborative Learning for Debiased Recommendations
- Online Low Rank Matrix Completion
- StableDR: Stabilized Doubly Robust Learning for Recommendation on Data Missing Not at Random
- MaskFusion: Feature Augmentation for Click-Through Rate Prediction via Input-adaptive Mask Fusion
2022
SIGIR 2022
- Decoupled Side Information Fusion for Sequential Recommendation
- Hierarchical Multi-Task Graph Recurrent Network for Next POI Recommendation
- Interpolative Distillation for Unifying Biased and Debiased Recommendation
- Locality-Sensitive State-Guided Experience Replay Optimization for Sparse-Reward in Online Recommendation
- Unify Local and Global Information for Top-N Recommendation
- Co-training Disentangled Domain Adaptation Network for Leveraging Popularity Bias in Recommenders
- User-Aware Multi-Interest Learning for Candidate Matching in Recommenders
- Post Processing Recommender Systems with Knowledge Graphs for Recency, Popularity, and Diversity of Explanations
- Multi-Level Interaction Reranking with User Behavior History
- User-controllable Recommendation Against Filter Bubbles
- DisenCDR: Learning Disentangled Representations for Cross-Domain Recommendation
- Thinking inside The Box: Learning Hypercube Representations for Group Recommendation
- A Review-aware Graph Contrastive Learning Framework for Recommendation
- Are Graph Augmentations Necessary? Simple Graph Contrastive Learning for Recommendation
- On-Device Next-Item Recommendation with Self-Supervised Knowledge Distillation
- Multi-Agent RL-based Information Selection Model for Sequential Recommendation
- Knowledge Graph Contrastive Learning for Recommendation
- Enhancing CTR Prediction with Context-Aware Feature Representation Learning
- Joint Multisided Exposure Fairness for Recommendation
- When Multi-Level Meets Multi-Interest: A Multi-Grained Neural Model for Sequential Recommendation
- Rethinking Reinforcement Learning for Recommendation: A Prompt Perspective
- Single-shot Embedding Dimension Search in Recommender System
- Learning to Infer User Implicit Preference in Conversational Recommendation
- Doubly-Adaptive Reinforcement Learning for Cross-Domain Interactive Recommendation
- An Attribute-Driven Mirroring Graph Network for Session-based Recommendation
- Geometric Disentangled Collaborative Filtering
- Hypergraph Contrastive Collaborative Filtering
- Multi-level Cross-view Contrastive Learning for Knowledge-aware Recommender System
- User-Centric Conversational Recommendation with Multi-Aspect User Modeling
- MGPolicy: Meta Graph Enhanced Off-policy Learning for Recommendations
- HIEN: Hierarchical Intention Embedding Network for Click-Through Rate Prediction
- Webformer: Pre-training with Web Pages for Information Retrieval
- Forest-based Deep Recommender
- Bilateral Self-unbiased Recommender Learning from Biased Implicit Feedback
- Price DOES Matter! Modeling Price and Interest Preferences in Session-based Recommendation
- Privacy-Preserving Synthetic Data Generation for Recommendation
- Investigating Accuracy-Novelty Performance for Graph-based Collaborative Filtering
- DAWAR: Diversity-aware Web APIs Recommendation for Mashup Creation based on Correlation Graph
- Variational Reasoning about User Preferences for Conversational Recommendation
- Alleviating Spurious Correlations in Knowledge-aware Recommendations through Counterfactual Generator
- NAS-CTR: Efficient Neural Architecture Search for Click-Through Rate Prediction
- Exploiting Variational Domain-Invariant User Embedding for Partially Overlapped Cross Domain Recommendation
- Analyzing and Simulating User Utterance Reformulation in Conversational Recommender Systems
- HAKG: Hierarchy-Aware Knowledge Gated Network for Recommendation
- Self-Guided Learning to Denoise for Robust Recommendation
- AutoGSR: Neural Architecture Search for Graph-based Session Recommendation
- Learning Graph-based Disentangled Representations for Next POI Recommendation
- GETNext: Trajectory Flow Map Enhanced Transformer for Next POI Recommendation
- Ada-Ranker: A Data Distribution Adaptive Ranking Paradigm for Sequential Recommendation
- Learning to Denoise Unreliable Interactions for Graph Collaborative Filtering
- INMO: A Model-Agnostic and Scalable Module for Inductive Collaborative Filtering
- ProFairRec: Provider Fairness-aware News Recommendation
- Multi-Faceted Global Item Relation Learning for Session-Based Recommendation
- ReCANet: A Repeat Consumption-Aware Neural Network for Next Basket Recommendation in Grocery Shopping
- Neighbour Interaction based Click-Through Rate Prediction via Graph-masked Transformer
- CAPTOR: A Crowd-Aware Pre-Travel Recommender System for Out-of-Town Users
- Multi-Behavior Sequential Transformer Recommender
- Deployable and Continuable Meta-Learning-Based Recommender System with Fast User-Incremental Updates
- Explainable Fairness for Feature-aware Recommender Systems
- Graph Trend Filtering Networks for Recommendation
- AutoLossGen: Automatic Loss Function Generation for Recommender Systems
- Determinantal Point Process Set Likelihood-Based Loss Functions for Sequential Recommendation
- KETCH: Knowledge Graph Enhanced Thread Recommendation in Healthcare Forums
- CPFair: Personalized Consumer and Producer Fairness Re-ranking for Recommender Systems
- PEVAE: A hierarchical VAE for personalized explainable recommendation.
- Positive, Negative and Neutral: Modeling Implicit Feedback in Session-based News Recommendation
- Less is More: Reweighting Important Spectral Graph Features for Recommendation
RecSys 2022
- A GPU-specialized Inference Parameter Server for Large-Scale Deep Recommendation Models
- A User-Centered Investigation of Personal Music Tours
- Adversary or Friend? An adversarial Approach to Improving Recommender Systems
- Aspect Re-distribution for Learning Better Item Embeddings in Sequential Recommendation
- BRUCE – Bundle Recommendation Using Contextualized item Embeddings
- Bundle MCR: Towards Conversational Bundle Recommendation
- CAEN: A Hierarchically Attentive Evolution Network for Item-Attribute-Change-Aware Recommendation in the Growing E-commerce Environment
- Context and Attribute-Aware Sequential Recommendation via Cross-Attention
- Countering Popularity Bias by Regularizing Score Differences
- Defending Substitution-based Profile Pollution Attacks on Sequential Recommenders
- Denoising Self-Attentive Sequential Recommendation
- Don’t recommend the obvious: estimate probability ratios
- Dual Attentional Higher Order Factorization Machines
- Dynamic Global Sensitivity for Differentially Private Contextual Bandits
- EANA: Reducing Privacy Risk on Large-scale Recommendation Models
- Effective and Efficient Training for Sequential Recommendation using Recency Sampling
- Exploiting Negative Preference in Content-based Music Recommendation with Contrastive Learning
- Exploring the longitudinal effects of nudging on users’ music genre exploration behavior and listening preferences
- Fairness-aware Federated Matrix Factorization
- Fast And Accurate User Cold-Start Learning Using Monte Carlo Tree Search
- Global and Personalized Graphs for Heterogeneous Sequential Recommendation by Learning Behavior Transitions and User Intentions
- Identifying New Podcasts with High General Appeal Using a Pure Exploration Infinitely-Armed Bandit Strategy
- Learning Recommendations from User Actions in the Item-poor Insurance Domain
- Learning to Ride a Buy-Cycle: A Hyper-Convolutional Model for Next Basket Repurchase Recommendation
- MARRS: A Framework for multi-objective risk-aware route recommendation using Multitask-Transformer
- Modeling Two-Way Selection Preference for Person-Job Fit
- Modeling User Repeat Consumption Behavior for Online Novel Recommendation
- Multi-Modal Dialog State Tracking for Interactive Fashion Recommendation
- Off-Policy Actor Critic for Recommender Systems
- ProtoMF: Prototype-based Matrix Factorization for Effective and Explainable Recommendations
- RADio – Rank-Aware Divergence Metrics to Measure Normative Diversity in News Recommendations
- Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5)
- Reducing Cross-Topic Political Homogenization in Content-Based News Recommendation
- Self-Supervised Bot Play for Transcript-Free Conversational Recommendation with Rationales
- Solving Diversity-Aware Maximum Inner Product Search Efficiently and Effectively
- TinyKG: Memory-Efficient Training Framework for Knowledge Graph Neural Recommender Systems
- Toward Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity
- Towards Psychologically Grounded Dynamic Preference Models
- You Say Factorization Machine, I Say Neural Network – It’s All in the Activation
KDD 2022
- Comprehensive Fair Meta-learned Recommender System
- Graph-Flashback Network for Next Location Recommendation
- Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation
- GUIDE: Group Equality Informed Individual Fairness in Graph Neural Networks
- Detecting Arbitrary Order Beneficial Feature Interactions for Recommender Systems
- Practical Counterfactual Policy Learning for Top-K Recommendations
- Addressing Unmeasured Confounder for Recommendation with Sensitivity Analysis
- Towards Representation Alignment and Uniformity in Collaborative Filtering
- Knowledge-enhanced Black-box Attacks for Recommendations
- Towards Universal Sequence Representation Learning for Recommender Systems
- Towards Unified Conversational Recommender Systems via Knowledge-Enhanced Prompt Learning
- Debiasing Learning for Membership Inference Attacks Against Recommender Systems
- Debiasing the Cloze Task in Sequential Recommendation with Bidirectional Transformers
- User-Event Graph Embedding Learning for Context-Aware Recommendation
- Aligning Dual Disentangled User Representations from Ratings and Textual Content
- Fair Ranking as Fair Division: Impact-Based Individual Fairness in Ranking
- Make Fairness More Fair: Fair Item Utility Estimation and Exposure Re-Distribution
- Invariant Preference Learning for General Debiasing in Recommendation
- PARSRec: Explainable Personalized Attention-fused Recurrent Sequential Recommendation Using Session Partial Actions
- CrossCBR: Cross-view Contrastive Learning for Bundle Recommendation
- HICF: Hyperbolic Informative Collaborative Filtering
- Extracting Relevant Information from User’s Utterances in Conversational Search and Recommendation
- Counteracting User Attention Bias in Music Streaming Recommendation via Reward Modification
- Adversarial Gradient Driven Exploration for Deep Click-Through Rate Prediction
- Self-Supervised Hypergraph Transformer for Recommender Systems
- PinnerFormer: Sequence Modeling for User Representation at Pinterest
CIKM 2022
- A Biased Sampling Method for Imbalanced Personalized Ranking
- Accurate Action Recommendation for Smart Home via Two-Level Encoders and Commonsense Knowledge
- Adapting Triplet Importance of Implicit Feedback for Personalized Recommendation
- An Uncertainty-Aware Imputation Framework for Alleviating the Sparsity Problem in Collaborative Filtering
- Asymmetrical Context-aware Modulation for Collaborative Filtering Recommendation
- Automatic Meta-Path Discovery for Effective Graph-Based Recommendation
- Beyond Learning from Next Item: Sequential Recommendation via Personalized Interest Sustainabilit
- ContrastVAE: Contrastive Variational AutoEncoder for Sequential Recommendation
- Cross-Domain Aspect Extraction using Transformers Augmented with Knowledge Graphs
- Cross-domain Cross-architecture Black-box Attacks on Fine-tuned Models with Transferred Evolutionary Strategies
- Cross-domain Recommendation via Adversarial Adaptation
- Disentangling Past-Future Modeling in Sequential Recommendation via Dual Networks
- Domain-Agnostic Constrastive Representations for Learning from Label Proportions
- Dual-Task Learning for Multi-Behavior Sequential Recommendation
- Dynamic Causal Collaborative Filtering
- Dynamic Hypergraph Learning for Collaborative Filtering
- Graph Based Long-Term And Short-Term Interest Model for Click-Through Rate Prediction
- Gromov-Wasserstein Guided Representation Learning for Cross-Domain Recommendation
- Hierarchical Item Inconsistency Signal learning for Sequence Denoising in Sequential Recommendation
- Hierarchically Fusing Long and Short-Term User Interests for Click-Through Rate Prediction in Product Search
- HySAGE: A Hybrid Static and Adaptive Graph Embedding Network for Context-Drifting Recommendations
- ITSM-GCN: Informative Training Sample Mining for Graph Convolution Network-based Collaborative Filtering
- KuaiRec: A Fully-observed Dataset and Insights for Evaluating Recommender Systems
- MARIO: Modality-Aware Attention and Modality-Preserving Decoders for Multimedia Recommendation
- Memory Bank Augmented Long-tail Sequential Recommendation
- Multi-level Contrastive Learning Framework for Sequential Recommendation
- OptEmbed: Learning Optimal Embedding Table for Click-through Rate Prediction
- Quantifying and Mitigating Popularity Bias in Conversational Recommender Systems
- Review-Based Domain Disentanglement without Duplicate Users or Contexts for Cross-Domain Recommendation
- SVD-GCN: A Simplified Graph Convolution Paradigm for Recommendation
- Spatiotemporal-aware Session-based Recommendation with Graph Neural Networks
- MAE4Rec: Storage-saving Transformer for Sequential Recommendations
- Target Interest Distillation for Multi-Interest Recommendation
- The Interaction Graph Auto-encoder Network Based on Topology-aware for Transferable Recommendation
- Tiger: Transferable Interest Graph Embedding for Domain-Level Zero-Shot Recommendation
- Towards Principled User-side Recommender Systems
- Towards Understanding the Overfitting Phenomenon of Deep Click-Through Rate Models
- Two-level Graph Path Reasoning for Conversational Recommendation with User Realistic Preference
WSDM 2022
- Long Short-Term Temporal Meta-learning in Online Recommendation
- Multi-Sparse-Domain Collaborative Recommendation via Enhanced Comprehensive Aspect Preference Learning
- RecGURU: Adversarial Learning of Generalized User Representations for Cross-Domain Recommendation
- Personalized Transfer of User Preferences for Cross-domain Recommendation
- Graph Collaborative Reasoning
- Modeling Scale-free Graphs with Hyperbolic Geometry for Knowledge-aware Recommendation
- Enumerating Fair Packages for Group Recommendations
- Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation
- CAN: Feature Co-Action Network for Click-Through Rate Prediction
- VAE++: Variational AutoEncoder for Heterogeneous One-Class Collaborative Filtering
- On Sampling Collaborative Filtering Datasets
- Triangle Graph Interest Network for Click-through Rate Prediction
- Show Me the Whole World: Towards Entire Item Space Exploration for Interactive Personalized Recommendations
- S-Walk: Accurate and Scalable Session-based Recommendation with Random Walks
- Choosing the Best of Both Worlds: Diverse and Novel Recommendations through Multi-Objective Reinforcement Learning
- Modeling Users’ Contextualized Page-wise Feedback for Click-Through Rate Prediction in E-commerce Search
- Toward Pareto Efficient Fairness-Utility Trade-off in Recommendation through Reinforcement Learning
- Supervised Advantage Actor-Critic for Recommender Systems
- Heterogeneous Global Graph Neural Networks for Personalized Session-based Recommendation
- Personalized Long-distance Fuel-efficient Route Recommendation Through Historical Trajectories Mining
- C2-CRS: Coarse-to-Fine Contrastive Learning for Conversational Recommender System
- Reinforcement Learning over Sentiment-Augmented Knowledge Graphs towards Accurate and Explainable Recommendation
- A Cooperative Neural Information Retrieval Pipeline with Knowledge Enhanced Automatic Query Reformulation
- Profiling the Design Space for Graph Neural Networks based Collaborative Filtering
- Towards Unbiased and Robust Causal Ranking for Recommender Systems
- Learning Multi-granularity Consecutive User Intent Unit for Session-based Recommendation
- Contrastive Meta Learning with Behavior Multiplicity for Recommendation
WWW 2022
- Alleviating Cold-start Problem in CTR Prediction with A Variational Embedding Learning Framework
- A Model-Agnostic Causal Learning Framework for Recommendation using Search Data
- CAUSPref: Causal Preference Learning for Out-of-Distribution Recommendation
- FairGAN: GANs-based Fairness-aware Learning for Recommendations with Implicit Feedback
- Implicit User Awareness Modeling via Candidate Items for CTR Prediction in Search Ads
- Modeling User Behavior with Graph Convolution for Personalized Product Search
- Optimizing Rankings for Recommendation in Matching Markets
- PNMTA: A Pretrained Network Modulation and Task Adaptation Approach for User Cold-Start Recommendation
- Path Language Modeling over Knowledge Graphs for Explainable Recommendation
- Collaborative Filtering with Attribution Alignment for Review-based Non-overlapped Cross Domain Recommendation
- Differential Private Knowledge Transfer for Privacy-Preserving Cross-Domain Recommendation
- Will You Accept the AI Recommendation? Predicting Human Behavior in AI-Assisted Decision Making
- AutoField: Automating Feature Selection in Deep Recommender Systems
- CBR: Context Bias aware Recommendation for Debiasing User Modeling and Click Prediction
- Choice of Implicit Signal Matters: Accounting for User Aspirations in Podcast Recommendations
- Consensus Learning from Heterogeneous Objectives for One-Class Collaborative Filtering
- Cross Pairwise Ranking for Unbiased Item Recommendation
- Deep Unified Representation for Heterogeneous Recommendation
- Disentangling Long and Short-Term Interests for Recommendation
- Efficient Online Learning to Rank for Sequential Music Recommendation
- Fast Variational AutoEncoder with Inverted Multi-Index for Collaborative Filtering
- FeedRec: News Feed Recommendation with Various User Feedbacks
- Filter-enhanced MLP is All You Need for Sequential Recommendation
- FIRE: Fast Incremental Recommendation with Graph Signal Processing
- Generative Session-based Recommendation
- Graph Neural Transport Networks with Non-local Attentions for Recommender Systems
- Graph-based Extractive Explainer for Recommendations
- GSL4Rec: Session-based Recommendations with Collective Graph Structure Learning and Next Interaction Prediction
- Hypercomplex Graph Collaborative Filtering
- Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learning
- Intent Contrastive Learning for Sequential Recommendation
- Learn over Past, Evolve for Future: Search-based Time-aware Recommendation with Sequential Behavior Data
- Learning Robust Recommenders through Cross-Model Agreement
- Learning to Augment for Casual User Recommendation
- MCL: Mixed-Centric Loss for Collaborative Filtering
- MINDSim: User Simulator for News Recommenders
- Modality Matches Modality: Pretraining Modality-Disentangled Item Representations for Recommendation
- Multiple Choice Questions based Multi-Interest Policy Learning for Conversational Recommendation
- Mutually-Regularized Dual Collaborative Variational Auto-encoder for Recommendation Systems
- Off-policy Learning over Heterogeneous Information for Recommendation
- Rating Distribution Calibration for Selection Bias Mitigation in Recommendations
- Re4: Learning to Re-contrast, Re-attend, Re-construct for Multi-interest Recommendation
- Sequential Recommendation via Stochastic Self-Attention
- Sequential Recommendation with Decomposed Item Feature Routing
- Stochastic-Expert Variational Autoencoder for Collaborative Filtering
- Towards Automatic Discovering of Deep Hybrid Network Architecture for Sequential Recommendation
- Unbiased Sequential Recommendation with Latent Confounders
- A Contrastive Sharing Model for Multi-Task Recommendation
- Accurate and Explainable Recommendation via Review Rationalization
- Comparative Explanations of Recommendations
- Recommendation Unlearning
- STAM: A Spatiotemporal Aggregation Method for Graph Neural Network-based Recommendation
- VisGNN: Personalized Visualization Recommendation via Graph Neural Networks
- Who to Watch Next: Two-side Interactive Networks for Live Broadcast Recommendation
- Causal Representation Learning for Out-of-Distribution Recommendation
- End-to-end Learning for Fair Ranking Systems
- Following Good Examples – Health Goal-Oriented Food Recommendation based on Behavior Data
- Link Recommendations for PageRank Fairness
- DCAF-BERT: A Distilled Cachable Adaptable Factorized Model For Improved Ads CTR Prediction
- DC-GNN: Decoupled Graph Neural Networks for Improving and Accelerating Large-Scale E-commerce Retrieval