Generative Recommendation

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Overview

Generative recommendation studies how to produce personalized items or ranked lists directly from user histories and context, instead of scoring a fixed candidate set. Common approaches encode items as semantic IDs and train autoregressive Transformers or language models, while diffusion, flow-based generation, and continuous retrieval offer alternatives. Training combines next-item supervision with semantic or behavioral signals, and sometimes reinforcement learning; evaluation uses sequential benchmarks such as Amazon datasets alongside production A/B tests. A central challenge is balancing useful item representations and reachability—including for cold or long-tail items—with accuracy, fairness, and the latency demands of large-scale serving.

Latest papers

CardsList

107 papers11 papers in the last four weeks, down 15% on the four weeks before. 0.1% of all new papers.

  1. REGER: Modeling inter-item Relations with Semantic IDs for Generative Recommendation

    Oct 27, 2026Yuxi Huang, Silin Zhou, Chenhao Wang +5Generative RecommendationSemantic ID Recommendation

    University of Electronic Science and Technology of China

  2. JevRec: Linguistic Encoding with Jev-like Decision Modeling for LLM-based Generative Recommendation

    Oct 27, 2026Qiyong Zhong, Jiajie Su, Ming Yang +1Generative RecommendationLarge Language Model-Based Recommendation

    Zhejiang University, Hangzhou, China

  3. The Vocabulary Is Already Here: Adapting Pretrained Interpretable Features for Generative Recommendation

    Oct 27, 2026Ziluowen Luo, Ruochen Liu, Jun Yin +6Generative RecommendationSemantic ID Recommendation

    Central South University Changsha, Hunan, China · The Hong Kong University of Science and Technology (Guangzhou) Guangzhou, China · Hong Kong Polytechnic University Hongkong, China +4

  4. MuSID-KD: Multigranularity Knowledge Distillation for Generative Recommendation with Semantic IDs

    Oct 26, 2026Fengshi Zhang, Xiyan Ding, Shuxiao Xie +1Knowledge DistillationGenerative Recommendation

    East China Normal University Shanghai, China · Fudan University Shanghai, China

  5. Knowledge Distillation across Item and Code Spaces for Parallel Generative Recommendation

    Oct 23, 2026Yixuan Xu, Hailin Liu, Linxiang Peng +1Semantic ID RecommendationGenerative Recommendation

    The Hong Kong University of Science and Technology, Hong Kong, China · University of Science and Technology of China, Hefei, China

  6. TGR-EvoDAG: A DAG-based Multi-Agent Code Evolution Framework for Generative Recommendation on Tencent

    Oct 23, 2026Junlin He, Junzhang Zhu, Yudong Li +5Generative RecommendationLarge Language Model-Guided Optimization

    Platform and Content Group, Tencent, Shenzhen, China · The Hong Kong Polytechnic University, Hong Kong, China · McGill University, Montreal, Canada +1

  7. EASformer: Environment-Action-State Alignment for Industrial Generative Ranking

    Oct 20, 2026Bohao Li, DingLun Cao, Pengcheng Huang +11Learning to RankGenerative Recommendation

    Beihang University, Beijing, China · Harbin Institute of Technology, Shenzhen, China · Independent Researcher, Shanghai, China +1

  8. Neighborhood-Aware Unlearning for Generative Recommendation

    Oct 19, 2026Pierre Lubitzsch, Yubao Tang, Maarten de Rijke +1Machine UnlearningGenerative Recommendation

    BIFOLD & TU Berlin, Germany · University of Amsterdam, The Netherlands

  9. HASTE: Hierarchical and Attribute-aware Supervision for Generative Recommendation

    Oct 12, 2026Tripti Shukla, Shwetha Somasundaram, Akshat Gupta +3Long-Tail RecommendationRecommender Systems

    Glance Bengaluru, India · Glance Vilnius, Lithuania · Glance London, United Kingdom

  10. AlignPoison: Conditional Targeted Poisoning of Generative Recommenders via Decoding-Aligned Prefixes

    Oct 10, 2026Zhuoxuan Zhang, Jinhao Duan, Xinyu Zhao +7Data Poisoning AttacksGenerative Recommendation

    University of North Carolina at Chapel Hill · University of Notre Dame · Meta

  11. Beyond Semantic IDs: Finite-Beam Reachability and Continuous-Query Generation in Generative Recommendation

    Oct 9, 2026Yu Sun, Renkai Xiang, Zuodong Xiang +6Generative RecommendationSemantic ID Recommendation

    Corresponding author

  12. Training with Missed Targets in Generative Recommendation: Separating Supervision from Probability Competition

    Oct 7, 2026Xuesi Wang, Yangbin Shi, Xiaolin ZhengGenerative RecommendationLearning to Rank

    Independent Researcher Shanghai, China · Zhejiang University Hangzhou, China

  13. Neither Black nor White: Balancing Semantic and Collaborative Signals with Graph-Informed Semantic IDs (GrIS)

    Oct 1, 2026Aleksei Medvedev, Alejandro Ariza-Casabona, Steven Derby +3Semantic ID RecommendationGraph Clustering

    Huawei Ireland Research Centre Dublin, Ireland

  14. When More Data Is Not Enough: The Context-Sufficiency Frontier in Generative AI Personalization

    Sep 30, 2026Merieme Askour, Ayoub MerimiGenerative Recommendation

  15. FineSID: Scalable and Efficient Semantic Identifier Learning for Generative Recommendation

    Sep 29, 2026Song-Li Wu, Weinan Gan, Zhaocheng Du +2Semantic ID RecommendationVector Quantization

    Tsinghua University · Huawei Noah’s Ark Lab · University of Science and Technology of China

  16. Algorithmic Harms Associated with Generative Model-Augmented Recommendation Systems

    Sep 27, 2026Christine Herlihy, Xumei Xi, Shloka Desai +2Algorithmic FairnessGenerative Recommendation

    Pinterest, Inc. San Francisco, California, USA

  17. Nutri-ATLAS: Embodied Agent for Tabulated Lookup and Assistance for Smarter nutrition

    Sep 26, 2026Uttej Kallakuri, Boxun Hu, Ankur A. Butala +2Embodied AILLM Reasoning with Graphs

    Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218 USA · Geriatric Engineering at Johns Hopkins University, Baltimore, MD 21218 USA · Departments of Neurology and Neurosurgery, Johns Hopkins Medicine, Baltimore, MD 21287 USA

  18. T-RoPE: Time-Aware Rotary Position Embedding for Sequential Recommendation

    Sep 24, 2026Yang Liu, Noel Loo, Ali Khanafer +4Rotary Positional EmbeddingsSequential Recommendation

    Shopify · Massachusetts Institute of Technology · Liquid AI

  19. From Interests to Semantic IDs: Retrieval-Grounded Credit Assignment for Generative Recommendation

    Sep 24, 2026Mengdan Zhu, Yufan Zhao, Yao Zhao +5Semantic ID RecommendationCredit Assignment

    Emory University Atlanta, GA, USA · Microsoft Redmond, WA, USA · Cornell University Ithaca, NY, USA

  20. Learning Better Reasoning for Generative Recommendation with Semantic IDs

    Sep 24, 2026Mengdan Zhu, Yufan Zhao, Sophie Di +5Semantic ID RecommendationSequential Recommendation

    Emory University Atlanta, GA, USA · Microsoft Redmond, WA, USA · Cornell University Ithaca, NY, USA

  21. Cross-Country Code-Mixing for Generative Recommendation

    Sep 24, 2026Yuan Gao, Hao Deng, Haibo Xing +5Cross-Domain Transfer LearningGenerative Recommendation

    Alibaba International Digital Commerce Group Beijing, China · Alibaba International Digital Commerce Group Hangzhou, China

  22. "If I Had to Buy Just ONE: Galaxy S26 Ultra": Auditing AI-Generated Product Recommendations

    Sep 16, 2026Lucas G. Uberti-Bona Marin, Thales Bertaglia, Giovanni Astante +5Language Model Bias EvaluationLarge Language Model-Based Recommendation

    Law & Tech Lab, Maastricht University · Utrecht University · Social Computing Group, Department of Informatics, University of Zurich

  23. Generative Query Suggestion via Intent Coverage and Query-Level Credit Assignment

    Sep 16, 2026Xinpeng Liu, Lu Ma, Jiayi Qiao +6Generative Recommendation

    Peking University · Qwen Business Unit of Alibaba · National University of Singapore +1

  24. LIGE-GR: A Smooth Leap from Ranking to Generative Recommendation in the LLM Era

    Sep 16, 2026Venkat Srinivas, Chenzhang He, Sam Woodmansee +63Learning to RankRecommender Systems

  25. Self-Evolving Memory for Generative Recommendation

    Sep 14, 2026Xinyu Lin, Zhuosong Jiang, Zixiao Suo +12Memory-Augmented Neural NetworksRecommender Systems

    National University of Singapore · Meta AI

  26. Generate to Explore, Select to Exploit: Aligning LLM-based Headline Generation with Personalized Recommendation

    Sep 14, 2026Yi Chen, Rufeng Cheng, Qiang Xie +1RL for Language ModelsLLM Personalization

    Baidu Inc., Beijing, China

  27. Efficient Multimodal Generative Recommendation with Latent Narrative Reasoning

    Sep 13, 2026Chenxing Wang, Nantao Zheng, Hao Miao +5Multimodal RecommendationGenerative Recommendation

    Weixin Group, Tencent · The Hong Kong Polytechnic University

  28. OneLA: Scaling Linear-Attention Decoding to Large Beams in Generative Recommendation

    Sep 11, 2026Xiangrui Yang, Cheng Peng, Yunfeng Zhao +9Linear AttentionAutoregressive Decoding

    Kuaishou Technology China · Peking University China

  29. History-Conditioned Joint-Prefix Alignment for Generative Recommendation

    Aug 29, 2026Hongliang Sun, Lianjie Li, Bolin Zhang +3Generative RecommendationSequential Recommendation

    Department of Computer Science, Weihai & Qingdao Research Institute Harbin Institute of Technology Weihai, China

  30. Off-Policy Evaluation for Semantic ID Recommenders: Does the Model's Own Code Hierarchy Help?

    Aug 28, 2026Artem BetleiOff-Policy EvaluationSemantic ID Recommendation

    Criteo AI Lab Grenoble, France