Key papers

• RLHF Fine-Tuning of LLMs for Alignment with Implicit User Feedback in Conversational Recommenders (2025)
  Zhongheng Yang et al.
  7.99
• RecoWorld: Building Simulated Environments for Agentic Recommender Systems (2025)
  Fei Liu et al.
  6.45
• Dialogue to Discovery: Attribute-Aware Preference Elicitation for Conversational Product Search Assistants (2026)
  Sarthak Harne et al.
  6.11
• PERSCEN: Learning Personalized Interaction Pattern and Scenario Preference for Multi-Scenario Matching (2025)
  Haotong Du et al.
  6.01
• Bumblebee: Interleaved Mixed-Layer Building Blocks for Large-Scale Recommendation Systems (2026)
  David Bauer et al.
  4.95
• Grevo: A Unified Generative Recommendation Framework with Evolutionary Item Indexing (2026)
  Huanjie Wang et al.
  4.95
• Beyond Static Testbeds: An Interaction-Centric Agent Simulation Platform for Dynamic Recommender Systems (2025)
  Song Jin et al.
  4.87
• Leveraging the Power of Conversations: Optimal Key Term Selection in Conversational Contextual Bandits (2025)
  Maoli Liu et al.
  4.87
• Multimodal Fusion And Sparse Attention-based Alignment Model for Long Sequential Recommendation (2025)
  Yongrui Fu et al.
  4.53
• RecRec: Recursive Refinement for Sequential Recommendation (2026)
  Pervez Shaik et al.
  4.33
• NEXT: Reasoning-Driven Video Recommendation via a Vision-Language Model (2026)
  Yuming Liu et al.
  4.33
• REPREC: Representation Driven Parameter-Efficient Recommendation System (2026)
  Harshini Kavuru et al.
  4.33
• Reward Guided Decoding for Generative Recommendation (2026)
  Ruochen Yang et al.
  4.33
• Sharpness-aware Model Merging with Salience Recovery for LLM-based Cross-Domain Sequential Recommendation (2026)
  Huwei Ji et al.
  4.33
• RecoReward: Recommender-Guided Multimodal Description Generation for Recommendation (2026)
  Guohong Mu et al.
  4.33
• DMF: A Deterministic Memory Framework for Conversational AI Agents (2026)
  Matteo Stabile et al.
  4.27
• MARS: Multi-rate Aggregation of Recency Signals for Sequential Recommendation across Sparse and Dense Regimes (2026)
  Zhenyu Yu et al.
  4.27
• When Does Latent Reasoning Help? MeRa: Metric-Space Bias for Spatial Prediction (2026)
  Zhenyu Yu et al.
  4.27
• Time-Constrained Recommendations: Reinforcement Learning Strategies for E-Commerce (2025)
  Sayak Chakrabarty and Souradip Pal
  4.09
• Cognitive-Aligned Spatio-Temporal Large Language Models For Next Point-of-Interest Prediction (2025)
  Penglong Zhai et al.
  3.97
• SIDE: Semantic ID Embedding for effective learning from sequences (2025)
  Dinesh Ramasamy et al.
  3.75
• Entire Space Counterfactual Learning for Reliable Content Recommendations (2022)
  Hao Wang et al.
  3.58
• DynaKRAG: A Unified Framework for Learnable Evidence Control in Multi-Hop Retrieval-Augmented Generation (2026)
  Yaqi Wu et al.
  3.45
• Not Only NTP: Extending Training Signal Coverage for Generative Recommendation (2026)
  Changhao Li et al.
  3.45
• Where Reasoning Matters: Rethinking Latent Reasoning in Semantic ID-based Generative Recommendation (2026)
  Shangxin Yang et al.
  3.45
• Learning to Forget: Satiation-Aware Long-Sequence Transducers for Mitigating Post-Purchase Redundancy (2026)
  Yipin Dai et al.
  3.45
• RecRec: Latent Interests Recursive Reasoning for Sequential Recommendation (2026)
  Wenhao Deng et al.
  3.45
• SPARC: Sequence-aware Progressive Attribute Routing and Compression Framework for Generative Recommendation (2026)
  Chang Liu et al.
  3.45
• On the Memorization Behavior of LLMs in Generative Recommendation: Observations, Implications, and Training Strategies (2026)
  Sunwoo Kim et al.
  3.39
• Do Generative Recommenders Deepen the Information Cocoon? A Closed-Loop Simulation with LLM-powered User Simulators (2026)
  Jiyuan Yang et al.
  3.39
• Intention Knowledge Graph Construction for User Intention Relation Modeling (2024)
  Jiaxin Bai et al.
  3.26
• Multi-User Contextual Cascading Bandits for Personalized Recommendation (2025)
  Jiho Park et al.
  2.93
• Graph Neural Network Enhanced Sequential Recommendation Method for Cross-Platform Ad Campaign (2025)
  Xiang Li et al.
  2.87
• Large Language Model-Enhanced Reinforcement Learning for Diverse and Novel Recommendations (2025)
  Jiin Woo et al.
  2.87
• Enhancing Personalized Multi-Turn Dialogue with Curiosity Reward (2025)
  Yanming Wan et al.
  2.71
• Interactive Visualization Recommendation with Hier-SUCB (2025)
  Songwen Hu et al.
  2.60
• ProReco: A Process Discovery Recommender System (2025)
  Tsung-Hao Huang et al.
  2.60
• Long-term User Engagement Optimization through Model-agnostic Downstream Rewards Learning (2026)
  Dingsu Wang et al.
  1.94
• Agentic Recommender System with Hierarchical Belief-State Memory (2026)
  Xiang Shen et al.
  1.89
• Beyond Retrieval: Learning Compact User Representations for Scalable LLM Personalization (2026)
  Heng Cao et al.
  1.89
• ChronoID: Infusing Explicit Temporal Signals into Semantic IDs for Generative Recommendation (2026)
  Dongdong Nian et al.
  1.89
• HoloRec: Holistic Encoding and Interleaved Reasoning for Generative Recommendation (2026)
  Shuqi Zhao et al.
  1.89
• One Sequential Recommendation Model Pretrained from Synthetic Priors Predicts Multiple Datasets (2026)
  Woosung Kang et al.
  1.89
• Harmonizing Semantic and Collaborative in LLMs: Reasoning-based Embedding Generator for Sequential Recommendation (2026)
  Qidong Liu et al.
  1.89
• Adaptive E-Learning Path Recommendation System Using Probabilistic Reinforcement Learning and Generative AI Explanations (2026)
  Alekhya Duggirala et al.
  1.89
• FASR: A Future-Aware and Smooth Rhythm-Aware Time-Gated GRU for Sequential Recommendation (2026)
  Peihua Zou et al.
  1.89
• RAGR: Review-Augmented Generative Recommendation (2026)
  Yingyi Zhang et al.
  1.83
• MMP-Refer: Multimodal Path Retrieval-augmented LLMs For Explainable Recommendation (2026)
  Xiangchen Pan et al.
  1.78
• AdaptFuse: Training-Free Sequential Preference Learning via Externalized Bayesian Inference (2026)
  Fangzhou Lin et al.
  1.78
• Long-Term Embeddings for Balanced Personalization (2026)
  Andrii Dzhoha and Egor Malykh
  1.78
• Unbiased Rectification for Sequential Recommender Systems Under Fake Orders (2026)
  Qiyu Qin et al.
  1.78
• Where and What: Reasoning Dynamic and Implicit Preferences in Situated Conversational Recommendation (2026)
  Dongding Lin et al.
  1.78
• Prompt-Unknown Promotion Attacks against LLM-based Sequential Recommender Systems (2026)
  Yuchuan Zhao et al.
  1.78
• Factorized Latent Reasoning for LLM-based Recommendation (2026)
  Tianqi Gao et al.
  1.78
• MealRec: Multi-granularity Sequential Modeling via Hierarchical Diffusion Models for Micro-Video Recommendation (2026)
  Xinxin Dong et al.
  1.72
• Fairness Begins with State: Purifying Latent Preferences for Hierarchical Reinforcement Learning in Interactive Recommendation (2026)
  Yun Lu et al.
  1.72
• AgenticRec: End-to-End Tool-Integrated Policy Optimization for Ranking-Oriented Recommender Agents (2026)
  Tianyi Li et al.
  1.72
• Intelligent Front-End Personalization: AI-Driven UI Adaptation (2026)
  Mona Rajhans
  1.67
• Reasoning-guided Collaborative Filtering with Language Models for Explainable Recommendation (2026)
  Fahad Anwaar et al.
  1.67
• Enhancing Bandit Algorithms with LLMs for Time-varying User Preferences in Streaming Recommendations (2026)
  Chenglei Shen et al.
  1.67