User Preference Modeling

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24 papers in the last four weeks, up 60% on the four weeks before. 0.2% of all new papers.

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Latest papers 163

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UxSID: Semantic-Aware User Interests Modeling for Ultra-Long Sequence
May 9, 2026Hongwei Zhang, Qiqiang Zhong, Jiangxia Cao +8Semantic ID Recommendation Sequential Recommendation
Kuaishou Technology, Beijing, China
Embeddings for Preferences, Not Semantics
May 8, 2026Carter Blair, Ariel D. Procaccia, Milind TambeText Embeddings Word Embeddings
Harvard University
CLIPer: Tailoring Diverse User Preference via Classifier-Guided Inference-Time Personalization
May 8, 2026Jinyan Su, Jinpeng Zhou, Claire Cardie +1Language Model Steering LLM Personalization
Cornell University
Bridging Textual Profiles and Latent User Embeddings for Personalization
May 7, 2026Zhaoxuan Tan, Xiang Zhai, Yan Zhu +2Sequential Recommendation Recommender Systems
University of Notre Dame · 2Google · * This work was done while Zhaoxuan was a student researcher at Google.
PREFER: Personalized Review Summarization with Online Preference Learning
May 7, 2026Millend Roy, Agostino Capponi, Vineet GoyalText Summarization E-Commerce
Department of Industrial Engineering and Operations Research Columbia University New York, NY 10027
FEDIN: Frequency-Enhanced Deep Interest Network for Click-Through Rate Prediction
May 3, 2026Zenan Dai, Jinpeng Wang, Junwei Pan +3Sequential Recommendation Frequency-Domain Feature Learning
Tsinghua University Shenzhen, China · Harbin Institute of Technology, Shenzhen Shenzhen, China · Tencent Shenzhen, China
Adaptive Querying with AI Persona Priors
May 1, 2026Kaizheng Wang, Yuhang Wu, Assaf ZeeviLatent Variable Models Bayesian Experimental Design
Department of Industrial Engineering and Operations Research and Data Science Institute, Columbia University. · Decision, Risk, and Operations Division, Columbia Business School.
DynamicPO: Dynamic Preference Optimization for Recommendation
May 1, 2026Xingyu Hu, Kai Zhang, Jiancan Wu +7Hard Negative Mining Preference Optimization
University of Science and Technology of China, Hefei, China · Shanghai Innovation Institute, Shanghai, China · Meituan, Chengdu, China
When Agents Shop for You: Role Coherence in AI-Mediated Markets
Apr 29, 2026Soogand Alavi, Salar NozariPrivacy Leakage in Language Models Agentic Commerce
Tippie College of Business, University of Iowa
Action-Aware Generative Sequence Modeling for Short Video Recommendation
Apr 28, 2026Wenhao Li, Zihan Lin, Zhengxiao Guo +7Sequential Recommendation User Preference Modeling
Kuaishou Inc. · Beijing, China · Unaffiliated +2
Probably Approximately Consensus: On the Learning Theory of Finding Common Ground
Apr 23, 2026Carter Blair, Ben Armstrong, Shiri Alouf-Heffetz +2User Preference Modeling Preference Learning
University of Waterloo · Tulane University · Ben Gurion University +1
Pre-trained LLMs Meet Sequential Recommenders: Efficient User-Centric Knowledge Distillation
Apr 23, 2026Nikita Severin, Danil Kartushov, Vladislav Urzhumov +8Sequential Recommendation Language Model Distillation
Independent researcher, Belgrade, Serbia · ITMO University, Saint Petersburg, Russia · Innopolis University, Innopolis, Russia +3
Align Generative Artificial Intelligence with Human Preferences: A Novel Large Language Model Fine-Tuning Method for Online Review Management
Apr 23, 2026Yanan Wang, Yong GeLLM Hallucination Mitigation LLM Fine-Tuning
Department of Information Systems and Operations Management, The University of Texas at Arlington · Department of Management Information Systems, University of Arizona
Where and What: Reasoning Dynamic and Implicit Preferences in Situated Conversational Recommendation
Apr 22, 2026Dongding Lin, Jian Wang, Yongqi Li +1Recommender Systems Large Language Model-Based Recommendation
Department of Computing, The Hong Kong Polytechnic University · College of Computer Science, Sichuan University
Vibrotactile Preference Learning: Uncertainty-Aware Preference Learning for Personalized Vibration Feedback
Apr 22, 2026Rongtao Zhang, Xin Zhu, Masoume Pourebadi Khotbehsara +3Pairwise Preference Learning Haptic Feedback
Department of Computer Science University of Southern California Los Angeles, California, USA
PREF-XAI: Preference-Based Personalized Rule Explanations of Black-Box Machine Learning Models
Apr 21, 2026Salvatore Greco, Jacek Karolczak, Roman Słowiński +1Explainable Artificial Intelligence User Preference Modeling
University of Catania, Department of Economics and Business, Corso Italia 55, Catania, 95129, Italy · Poznan University of Technology, Institute of Computing Science,2026 Piotrowo 2, Poznań, 60-965, Poland · bPoznan University of Technology, Institute of Computing Science,2026 Piotrowo 2, Poznań, 60-965, Poland +1
Personalized Benchmarking: Evaluating LLMs by Individual Preferences
Apr 21, 2026Cristina Garbacea, Heran Wang, Chenhao TanLLM Evaluation User Preference Modeling
University of Chicago
Decisive: Guiding User Decisions with Optimal Preference Elicitation from Unstructured Documents
Apr 20, 2026Akriti Jain, Anish Mulay, Divyansh Verma +3AI-Assisted Decision Making Human-AI Decision Making
Adobe Research, India · IIT Madras · Work done during internship at Adobe Research +4
Latent Preference Modeling for Multi-Session Personalized Tool Calling
Apr 20, 2026Yejin Yoon, Minseo Kim, Taeuk KimLLM Personalization LLM Agent Memory
Hanyang University, Seoul, Republic of Korea
HorizonBench: Long-Horizon Personalization with Evolving Preferences
Apr 19, 2026Shuyue Stella Li, Bhargavi Paranjape, Kerem Oktar +9Long-Context Modeling User Preference Modeling
University of Washington · Meta · OpenAI +1
From "Strings" to "Things" for Personal Knowledge Graphs: Evaluating LLM Triple Extraction for Recommendation Systems
Apr 18, 2026Abhirup Dasgupta, Fernando Spadea, Oshani SeneviratneKG Construction Knowledge Representation
Rensselaer Polytechnic Institute, Troy NY 12180, USA
Learning Behaviorally Grounded Item Embeddings via Personalized Temporal Contexts
Apr 16, 2026Rafael T. Sereicikas, Pedro R. Pires, Gregorio F. Azevedo +1Sequential Recommendation Recommender Systems
Federal University of São Carlos · Sorocaba, São Paulo, Brazil
GenRec: A Preference-Oriented Generative Framework for Large-Scale Recommendation
Apr 16, 2026Yanyan Zou, Junbo Qi, Lunsong Huang +7Generative Retrieval Recommender Systems
JD.com Beijing, China · Waseda University Tokyo, Japan
CoPA: Benchmarking Personalized Question Answering with Data-Informed Cognitive Factors
Apr 16, 2026Hang Su, Zequn Liu, Chen Hu +3LLM Personalization Question Answering
East China Normal University, China · Zhongguancun Academy, China
CPGRec+: A Balance-oriented Framework for Personalized Video Game Recommendations
Apr 16, 2026Xiping Li, Aier Yang, Jianghong Ma +4Graph Neural Networks Recommender Systems
Harbin Institute of Technology, China · School of Computer Science, Wuhan University, China
Efficient Personalization of Generative User Interfaces
Apr 10, 2026Yi-Hao Peng, Jeffrey P. Bigham, Jason WuPairwise Preference Learning Human Preference Modeling
Massachusetts Institute of Technology · Carnegie Mellon University · Purdue University
Towards Natural Personalization: Evaluating Long-Horizon Preference Following in Personalized User-LLM Interactions
Mar 4, 2026Qianyun Guo, Yibo Li, Yue Liu +1LLM Evaluation LLM Personalization
National University of Singapore, Singapore.
IDProxy: CTR Prediction with Multimodal LLMs for Cold-Start Recommendation at Xiaohongshu
Mar 2, 2026Yubin Zhang, Haiming Xu, Guillaume Salha-Galvan +6Cold-Start Recommendation Multimodal Embedding
Xiaohongshu Inc. Shanghai, China · Shanghai Jiao Tong University Shanghai, China · Fudan University Shanghai, China
HiSAC: Hierarchical Sparse Activation Compression for Ultra-long Sequence Modeling in Recommenders
Feb 24, 2026Kun Yuan, Junyu Bi, Daixuan Cheng +5Sequential Recommendation Hierarchical Representation Learning
Alibaba Group · Beijing, China · Renmin University
Do Implicit Personalization and Explicit Styles Conflict? PsPLUG: A Lightweight Plug-in for Balancing Personalization and Style in Customized LLMs
Jan 10, 2026Yutong Song, Jiang Wu, Shaofan Yuan +5LLM Personalization Controllable Text Generation
University of California, Irvine · Independent Researcher · TikTok
Who Laughs with Whom? Disentangling Influential Factors in Humor Preferences across User Clusters and LLMs
Jan 6, 2026Soichiro Murakami, Hidetaka Kamigaito, Hiroya Takamura +1LLM Evaluation Human Preference Modeling
CyberAgent · Nara Institute of Science and Technology · Institute of Science Tokyo
P-Check: Advancing Personalized Reward Model via Learning to Generate Dynamic Checklist
Jan 6, 2026Kwangwook Seo, Dongha LeeReward Modeling User Preference Modeling
Department of Artificial Intelligence,Yonsei University
PreferThinker: Reasoning-based Personalized Image Preference Assessment
Nov 1, 2025Shengqi Xu, Xinpeng Zhou, Yabo Zhang +6Preference Optimization User Preference Modeling
♠Fudan University · ♣Harbin Institute of Technology · ♦iN2X
GMTRouter: Personalized LLM Router over Multi-turn User Interactions
Oct 29, 2025Yihang Sun, Encheng Xie, Tao Feng +1LLM Personalization LLM Routing
University of Illinois Urbana-Champaign
POPI: Personalizing LLMs via Optimized Natural Language Preference Inference
Oct 17, 2025Yizhuo Chen, Xin Liu, Ruijie Wang +7LLM Personalization Personalized Language Models
University of Illinois Urbana-Champaign · Amazon · University of Notre Dame
Algorithmic Shortlisting in Participatory Budgeting
Aug 7, 2025Juan Ignacio Zambrano, Clément Contet, Jairo Gudiño-Rosero +3Learning to Rank Privacy-Preserving ML
IRIT · Université Toulouse Capitole · Université de Toulouse +3
MiCRo: Mixture Modeling and Context-aware Routing for Personalized Preference Learning
May 30, 2025Jingyan Shen, Jiarui Yao, Rui Yang +5Pairwise Preference Learning Reward Modeling
New York University · University of Illinois Urbana-Champaign · Rice University
Modeling and Optimizing User Preferences in AI Copilots: A Comprehensive Survey and Taxonomy
May 28, 2025Saleh Afzoon, Ali Shahsavandi, Phuong Thao Huynh +4LLM Personalization Human-AI Interaction
School of Computing, Macquarie University, Sydney, Australia · Department of Computer Engineering and Information Technology, Shiraz University of Technology, Shiraz, Iran
LatentCRS: A Variational EM Framework for Bridging Semantics and Behavior in LLM-based Conversational Recommendation
Mar 12, 2025Guanrong Li, Kuo Tian, Jinnan Qi +4Recommender Systems Large Language Model-Based Recommendation
Nanjing University Nanjing, Jiangsu, China
Inferring the Unspoken: Aligning Embodied Agents with Implicit Preferences
Feb 2, 2025Manjie Xu, Xinyi Yang, Wei Liang +2User Preference Modeling Preference Learning
Institute for Artificial Intelligence, Peking University · School of Psychological and Cognitive Sciences, Peking University · School of Intelligence Science and Technology, Peking University +5
Learning Consumer Preferences from Bundle Sales Data
Sep 11, 2022Ningyuan Chen, Setareh Farajollahzadeh, Qingwei Jin +2User Preference Modeling
University of Toronto · McGill University · Zhejiang University
PACIFIC: Can LLMs Discern the Psychometric Traits Influencing Your Preferences? Personality-Driven Preference Alignment in LLMs
Date pendingTianyu Zhao, Siqi Li, Yasser Shoukry +1LLM Personalization Preference Alignment
Department of Electrical Engineering and Computer Science University of California, Irvine Irvine, CA 92697, USA
Toward Collective-Centric Evaluation of Preference Inference for Participatory Democracy
Date pendingPierre-Antoine Lequeu, Salim Hafid, Paul Lerner +6User Preference Modeling Preference Learning
Sorbonne Université, CNRS, ISIR, Paris, France · Sciences Po, médialab, Paris, France · Sorbonne Université, STIH/CERES, Paris, France

May 9, 2026, cs.AIJ/K move · Enter open · S save

UxSID: Semantic-Aware User Interests Modeling for Ultra-Long Sequence

Hongwei Zhang, Qiqiang Zhong, Jiangxia Cao, Yiyang Lv+7

Kuaishou Technology, Beijing, China

Semantic ID Recommendation Sequential Recommendation User Preference Modeling Sequence Modeling

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Modeling ultra-long user sequences involves a difficult trade-off between efficiency and effectiveness. While current paradigms rely on either item-specific search or item-agnostic compression, we propose UxSID, a framework exploring a third path: semantic-group shared interest memory. By utilizing Semantic IDs (SIDs) and a dual-level attention strategy, UxSID captures target-aware preferences without the heavy cost of item-specific models. This end-to-end architecture balances computational parsimony with semantic awareness, achieving state-of-the-art performance and a 0.337% revenue lift in large-scale advertising A/B test.

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Latest papers 163