Large Language Model-Based Recommendation

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Overview

The field studies how language models can use item descriptions, interaction histories, and conversational feedback to predict and explain what people may want. Common approaches include instruction-tuned or reinforcement-trained recommenders, retrieval-augmented generation, semantic item IDs, and hybrids that combine language representations with collaborative filtering or graph signals. Work spans sequential and conversational recommendation, cold-start retrieval, and large-scale search and feeds, with distillation and offline feature generation used to reduce serving costs. A central tension is that semantic reasoning and fluent explanations do not guarantee accurate, grounded recommendations: candidate retrieval, user-data alignment, bias, safety, and latency remain important challenges.

Latest papers

CardsList

213 papers18 papers in the last four weeks, down 18% on the four weeks before. 0.1% of all new papers.

  1. An Investigation of Linguistic Biases in LLM-Based Recommendations

    Apr 28, 2026Nitin Venkateswaran, Jason Ang, Deep Adhikari +1Language Model Bias EvaluationLinguistic Bias in Language Models

    University of Florida

  2. Pre-trained LLMs Meet Sequential Recommenders: Efficient User-Centric Knowledge Distillation

    Apr 23, 2026Nikita Severin, Danil Kartushov, Vladislav Urzhumov +8Sequential RecommendationLanguage Model Distillation

    Independent researcher, Belgrade, Serbia · ITMO University, Saint Petersburg, Russia · Innopolis University, Innopolis, Russia +3

  3. Enhancing Online Recruitment with Category-Aware MoE and LLM-based Data Augmentation

    Apr 23, 2026Minping Chen, Bing Xu, Zulong Chen +4Data AugmentationMixture of Experts

    HKUST (GZ) · Alibaba Group · Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ) +3

  4. On Reasoning Behind Next Occupation Recommendation

    Apr 23, 2026Shan Dong, Palakorn Achananuparp, Hieu Hien Mai +3Large Language Model-Based RecommendationLanguage Model Post-Training

    Singapore Management University · Columbia University

  5. Where and What: Reasoning Dynamic and Implicit Preferences in Situated Conversational Recommendation

    Apr 22, 2026Dongding Lin, Jian Wang, Yongqi Li +1Recommender SystemsLarge Language Model-Based Recommendation

    Department of Computing, The Hong Kong Polytechnic University · College of Computer Science, Sichuan University

  6. Modular Representation Compression: Adapting LLMs for Efficient and Effective Recommendations

    Apr 20, 2026Yunjia Xi, Menghui Zhu, Jianghao Lin +4LLM CompressionEmbedding Compression

    Shanghai Jiao Tong University Shanghai, China · Huawei Noah’s Ark Lab Shanghai, China · Antai College of Economics and Management, Shanghai Jiao Tong University Shanghai, China

  7. GraphLoRA: Structure-Aware Low-Rank Adaptation for Large Language Model Recommendation

    Apr 20, 2026Lin Mu, Guoji Wang, Li Ni +4Low-Rank AdaptationLarge Language Model-Based Recommendation

    Anhui University · Hefei University · University of Science and Technology of China

  8. Polarization by Default: Auditing Recommendation Bias in LLM-Based Content Curation

    Apr 17, 2026Nicolò Pagan, Christopher Barrie, Chris Andrew Bail +1LLM PromptingSocial Bias in Language Models

    University of Zurich, Department of Informatics, Zurich, CH · New York University, Department of Sociology, New York, USA · University of Oxford, Department of Sociology, Oxford, UK +2

  9. GenRec: A Preference-Oriented Generative Framework for Large-Scale Recommendation

    Apr 16, 2026Yanyan Zou, Junbo Qi, Lunsong Huang +7RL for RecommendationGenerative Retrieval

    JD.com Beijing, China · Waseda University Tokyo, Japan

  10. Dual-Enhancement Product Bundling: Bridging Interactive Graph and Large Language Model

    Apr 15, 2026Zhe Huang, Peng Wang, Yan Zheng +2Large Language Model-Based Recommendation

  11. TRACE: A Conversational Framework for Sustainable Tourism Recommendation with Agentic Counterfactual Explanations

    Apr 14, 2026Ashmi Banerjee, Adithi Satish, Wolfgang Wörndl +1Large Language Model-Based RecommendationExplainable Recommendation

    Technical University of Munich, Munich, Germany · Polytechnic University of Bari, Bari, Italy

  12. Ads in AI Chatbots? An Analysis of How Large Language Models Navigate Conflicts of Interest

    Apr 9, 2026Addison J. Wu, Ryan Liu, Shuyue Stella Li +2LLM Decision-MakingLarge Language Model-Based Recommendation

    Princeton University · University of Washington

  13. ReRec: Reasoning-Augmented LLM-based Recommendation Assistant via Reinforcement Fine-tuning

    Apr 9, 2026Jiani Huang, Shijie Wang, Liangbo Ning +2Large Language Model-Based RecommendationRL Fine-Tuning

    The Hong Kong Polytechnic University

  14. Filling the Gaps: Selective Knowledge Augmentation for LLM Recommenders

    Apr 9, 2026Jaehyun Lee, Sanghwan Jang, SeongKu Kang +1Recommender SystemsLarge Language Model-Based Recommendation

    Pohang University of Science and Technology, Pohang, Republic of Korea · Korea University, Seoul, Republic of Korea

  15. AdaptFuse: Training-Free Sequential Preference Inference via Externalized Bayesian Computation

    Apr 5, 2026Fangzhou Lin, Zilin Dai, Shuo Xing +8Preference LearningLarge Language Model-Based Recommendation

    Texas A&M University · Worcester Polytechnic Institute · Tohoku University +1

  16. CURE:Circuit-Aware Unlearning for LLM-based Recommendation

    Apr 4, 2026Ziheng Chen, Jiali Cheng, Zezhong Fan +4Machine UnlearningLLM Unlearning

    Walmart Global Tech, Sunnyvale, CA, USA · University of Massachusetts Lowell, Lowell, MA, USA · Zhejiang University, Hangzhou, China +2

  17. Fusion and Alignment Enhancement with Large Language Models for Tail-item Sequential Recommendation

    Apr 4, 2026Zhifu Wei, Yizhou Dang, Guibing Guo +2Recommender SystemsSequential Recommendation

    Northeastern University, Shenyang, China · Tianjin University, Tianjin, China · Singapore University of Technology and Design, Singapore, Singapore

  18. Agent4POI: Agentic Context-Conditioned Affordance Reasoning for Multimodal Point-of-Interest Recommendation

    Apr 3, 2026Jinze Wang, Yangchen Zeng, Tiehua Zhang +5Recommender SystemsMultimodal Recommendation

    Tongji University · Swinburne University of Technology · Southeast University +4

  19. Synapse: Evolving Job-Person Fit with Explainable Two-phase Retrieval and LLM-guided Genetic Resume Optimization

    Apr 2, 2026Ansel Kaplan Erol, Seohee Yoon, Keenan Hom +1Job-Candidate MatchingRecommender Systems

    Georgia Institute of Technology, Atlanta, GA, USA

  20. Jump Start or False Start? A Theoretical and Empirical Evaluation of LLM-initialized Bandits

    Apr 2, 2026Adam Bayley, Xiaodan Zhu, Raquel Aoki +2Contextual BanditsLarge Language Model-Based Recommendation

    Department of Electrical and Computer Engineering, Queen’s University · RBC Borealis

  21. Grounded Token Initialization for New Vocabulary in LMs for Generative Recommendation

    Apr 2, 2026Daiwei Chen, Zhoutong Fu, Chengming Jiang +12Language Model Vocabulary ExpansionLarge Language Model-Based Recommendation

    University of Wisconsin-Madison · LinkedIn Corporation · Northeastern University +1

  22. Multi-Agent Video Recommenders: Evolution, Patterns, and Open Challenges

    Apr 2, 2026Srivaths Ranganathan, Abhishek Dharmaratnakar, Anushree Sinha +1Recommender SystemsMulti-Agent Collaboration

    Google LLC, Mountain View, USA · Google LLC, San Bruno, USA

  23. Towards Position-Robust Talent Recommendation via Large Language Models

    Apr 2, 2026Silin Du, Hongyan LiuRecommender SystemsLarge Language Model-Based Recommendation

    Department of Management Science and Engineering, Tsinghua University, Beijing, China.

  24. GISTBench: Evaluating LLM User Understanding via Evidence-Based Interest Verification

    Mar 31, 2026Iordanis Fostiropoulos, Muhammad Rafay Azhar, Abdalaziz Sawwan +8LLM EvaluationUser Modeling

    Meta Recommendation Systems (MRS)

  25. LLMAR: A Tuning-Free Recommendation Framework for Sparse and Text-Rich Industrial Domains

    Mar 25, 2026Ryogo Hishikawa, Ichiro Kataoka, Shinya YudaLLM-Assisted AnnotationRecommender Systems

    Hitachi, Ltd. Research and Development Group Hitachi, Ibaraki, Japan · Hitachi Power Solutions Co., Ltd. Hitachi, Ibaraki, Japan

  26. Lightweight Fairness for LLM-Based Recommendations via Kernelized Projection and Gated Adapters

    Mar 24, 2026Nan Cui, Wendy Hui Wang, Yue NingFairness in Recommender SystemsDemographic Bias in Language Models

    Department of Computer Science, Stevens Institute of Technology, Hoboken NJ, USA

  27. Reasoning over Semantic IDs Enhances Generative Recommendation

    Mar 24, 2026Yingzhi He, Yan Sun, Junfei Tan +6Large Language Model-Based RecommendationGenerative Recommendation

    National University of Singapore Singapore, Singapore · University of Science and Technology of China Hefei, China · Tencent Inc. Shenzhen, China

  28. KARMA: Knowledge-Action Regularized Multimodal Alignment for Personalized Search at Taobao

    Mar 24, 2026Zhi Sun, Wenming Zhang, Yi Wei +4Information RetrievalPersonalized Language Model Alignment

    Taobao & Tmall Group of Alibaba, Hangzhou, China

  29. AgenticRec: A Recommendation-Oriented Agentic Framework with Progressive Tool-Integrated Reasoning Optimization

    Mar 23, 2026Tianyi Li, Zixuan Wang, Guidong Lei +2Recommender SystemsLarge Language Model-Based Recommendation

    Xiamen University, Xiamen, China

  30. Causal Direct Preference Optimization for Distributionally Robust Generative Recommendation

    Mar 21, 2026Chu Zhao, Enneng Yang, Jianzhe Zhao +1Large Language Model-Based RecommendationDistribution Shift Robustness

    Northeastern University, Shenyang, China · Shenzhen Campus of Sun Yat-sen University, China