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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Personalized Image Aesthetic Assessment via Preference-rich Sample Mining and Cohort Merging
Jul 17, 2026Zhichao Yang, Tianjiao Gu, Zhixianhe Zhang +3Personalized Image Aesthetics Assessment Image Quality Assessment
Xidian University Xi’an, China · Xidian University Xian, China
Field-Aware RankMixer with Dual-Stream Bilinear Fusion for the Tencent UNI-REC Challenge
Jul 17, 2026Yufeng Zhang, Zhengqi Xu, Jiajun CuiFeature Interaction Modeling Recommender Systems
Independent Researcher · Meituan
From Feasibility to Desirability: Plan, Learn, Adapt (PLA) Framework for Personalized On-Device Itinerary Generation
Jul 17, 2026Himel Dev, Tanmoy Sen, Madhusudan Basak +1User Preference Modeling
Tech LLC · University of Virginia · University of Massachusetts Amherst
Deployable Human Preference Alignment in Robotics: Learning Representative Rewards from Diverse Human Preferences
Jul 14, 2026Taehyung Kim, Gwangmo Lee, Minjun Chang +2Clustering Preference Alignment
Yonsei University, Seoul, South Korea · Georgia Institute of Technology, United States of America · Hyundai Motor Company, Seoul, South Korea
SlimPer: Make Personalization Model Slim and Smart
Jul 14, 2026Siqi Wang, Xianjie Chen, Shaofeng Deng +42Learning to Rank Memory-Efficient Inference
RecRec: Recursive Refinement for Sequential Recommendation
Jul 12, 2026Pervez Shaik, Prosenjit Biswas, Abhinav Thorat +2Sequential Recommendation Iterative Refinement
Sony Research India India
APeB: Benchmarking Personalization Ability of Large Language Model Agents
Jul 3, 2026Garry Yang, Zizhe Chen, Xinru Chen +9LLM Personalization LLM Agent Evaluation
1The Chinese University of Hong Kong · 2ByteDance
PAPA: Online Personalized Active Preference Alignment
Jul 1, 2026Anindya Sarkar, Nasik Muhammad Nafi, Isaac Lyngaas +2Diffusion Model Alignment Diffusion Model Fine-Tuning
Washington University in St. Louis · Oak Ridge National Laboratory
Understanding Guest Preferences and Optimizing Two-sided Marketplaces: Airbnb as an Example
Jul 1, 2026Yufei Wu, Daniel SchmiererUser Preference Modeling
Airbnb, Inc. San Francisco, California, USA
Beyond expert users: agents should help users construct preferences, not just elicit them
Jun 29, 2026Irena Saracay, Ludwig Schmidt, Carlos GuestrinAI Agent Benchmarks Recommender Systems
Stanford University
SocialPersona: Benchmarking Personalized Profiling and Response with Multimodal Social-Media Context
Jun 25, 2026Qinkai Zhang, Yanyan Zhao, Xin Lu +3LLM Personalization Multimodal Large Language Models
Harbin Institute of Technology
TailorMind: Towards Preference-Aligned Multimodal Content Generation
Jun 22, 2026Hengji Zhou, Ye Liu, Yufeng Liu +3Multimodal Generation User Preference Modeling
1South China University of Technology · 2Harbin Institute of Technology, Shenzhen
Mitigating Early Training Collapse in CTR Models
Jun 20, 2026Ergun Biçici, Erkan ÇetinyamaçCTR Prediction Feature Selection
Intelligent Application Development, Huawei Türkiye R&D Center, Istanbul, Turkey
Structuring and Tokenizing Distributed User Interest Context for Generative Recommendation
Jun 18, 2026Ruizhong Qiu, Yinglong Xia, Dongqi Fu +6Sequential Recommendation User Modeling
University of Illinois Urbana–Champaign · 2Meta MRS
SAERec: Constructing Fine-grained Interpretable Intents Priors via Sparse Autoencoders for Recommendation
Jun 17, 2026Jiangnan Xia, Xuansheng Wu, Yu Yang +2Sequential Recommendation Recommender Systems
University of Georgia United States · Shanghai AI Laboratory China · The Education University of Hong Kong Hong Kong +2
ProfiLLM: Utility-Aligned Agentic User Profiling for Industrial Ride-Hailing Dispatch
Jun 17, 2026Tengfei Lyu, Zirui Yuan, Xu Liu +4User Modeling LLM Agent Training
HKUST(GZ) · Didichuxing Co. Ltd
Predictive Analytics in E-Commerce for CustomerBehavior Forecasting using hybrid Ret-DNN withXGBoost Model
Jun 16, 2026Degala Pushpa Sri, Mayank Atreya, Lakshmi. H +2E-Commerce User Preference Modeling
Department of MBA Pace Institute of Technology and Sciences Valluru, Ongole, Andhra Pradesh, India · Chewy Inc Atlanta, USA · Department of Management Studies Nitte Meenakshi Institute of Technology, Nitte (Deemed to be University) Bengaluru, India +2
MapSatisfyBench: Benchmarking Satisfaction-Aware Map Agents through Behavior-Grounded Implicit Decision Factors
Jun 16, 2026Lubin Bai, Mengyu Cao, Sixue Wang +5LLM Agent Evaluation User Preference Modeling
AMAP, Alibaba Group, Beijing, China · College of Urban and Environmental Sciences, Peking University, Beijing, China
ChatPlanner: A Large Language Model Framework for Personalized Public Transit Routing
Jun 13, 2026Tingting Yang, Chenhao Xue, Jun ChenIntelligent Transportation Systems LLM Routing
School of Engineering and Materials Science, Queen Mary University of London Mile End Road, London, E1 4NS, United Kingdom · Department of Engineering Science, University of Oxford Parks Road, Oxford, OX1 3PJ, United Kingdom
Group Preference Collapse in Personalized Multimodal Large Language Models
Jun 12, 2026Fan Lyu, Wenqi Zhang, Joost van de WeijerMultimodal Large Language Models Personalized Language Models
Computer Vision Center, Universitat Autònoma de Barcelona, Barcelona, Spain, 08193
Trait, Not State: The Durability of Reading Identity in Social Highlighting
Jun 11, 2026Kazuki Nakayashiki, Keisuke WatanabeInformation Retrieval User Preference Modeling
Glasp Inc.
Generative Archetype-Grounded Item Representations for Sequential Recommendation
Jun 9, 2026Yifan Li, Jiahong Liu, Xinni Zhang +5Sequential Recommendation Representation Learning
The Chinese University of Hong Kong Hong Kong SAR, China · McGill University Montreal, Canada · Tongji University Shanghai, China
Selection, Not Salience: The Shape and Limits of Personalization in Social Highlighting
Jun 9, 2026Kazuki Nakayashiki, Keisuke WatanabeLLM Personalization User Preference Modeling
Glasp Inc.
UXBench: Benchmarking User Experience in AI Assistants
Jun 8, 2026Mengze Hong, Xia Zeng, Zeyang Lei +13LLM Evaluation User Preference Modeling
Hong Kong Polytechnic University · Yuanbao Team, Tencent
Personal Salience: Highlighting Is Social, but Individuality Lives in Selection
Jun 8, 2026Kazuki Nakayashiki, Keisuke WatanabeLLM Personalization User Preference Modeling
Glasp Inc.
Provably Efficient Personalized Multi-Objective Bandits with Proactive Conversational Queries
Jun 7, 2026Linfeng Cao, Ming Shi, Ness B. ShroffMulti-Armed Bandits Combinatorial Multi-Armed Bandits
Department of Computer Science and Engineering, The Ohio State University · Department of Electrical Engineering, University at Buffalo · Department of Electrical and Computer Engineering, The Ohio State University
PAFO: Pareto Fairness Optimization for Personalized Reward Modeling
Jun 6, 2026Xiaoyan Zhao, Haoting Ni, Yang Zhang +3Reward Modeling LLM Alignment
National University of Singapore · University of Science and Technology of China · Peking University
PaperFlow: Profiling, Recommending, and Adapting Across Daily Paper Streams
Jun 5, 2026Fuqiang Wang, Song Tan, Zheng Guo +8Information Retrieval Recommender Systems
1Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan), Qilu University of Technology (Shandong Academy of Sciences) · University of Chinese Academy of Science · 3Shanghai Artificial Intelligence Laboratory
Mind the Gap: Bridging Behavioral Silos with LLMs in Multi-Vertical Recommendations
Jun 4, 2026Nimesh Sinha, Raghav Saboo, Martin Wang +1Cold-Start Recommendation Recommender Systems
DoorDash Inc. San Francisco, California, USA
Statistical Priors for Implicit Preferences: Decoupling Skill Selection as a Local Harness in Personal Agents
Jun 4, 2026Zeyu Gan, Huayi Tang, Yong LiuLLM Agents User Preference Modeling
Gaoling School of Artificial Intelligence Renmin University of China Beijing, China
Beyond Retrieval: Learning Compact User Representations for Scalable LLM Personalization
Jun 3, 2026Heng Cao, Fan Zhang, Jian Yao +8LLM Personalization Prompt Tuning
*Microsoft · †The Hong Kong Polytechnic University · ⋄Shanghai International Studies University +1
Sparse Mixture-of-Experts Reward Models Learn Interpretable and Specialized Experts for Personalized Preference Modeling
Jun 2, 2026Yifan Wang, Jinyi Mu, Mayank Jobanputra +5Pairwise Preference Learning Reward Modeling
Saarland University · Independent Researcher · Bielefeld University +2
Memory Retrieval for Changing Preferences
Jun 2, 2026Yuehan Qin, Li Li, Linxin Song +4Conversational Memory User Preference Modeling
University of Southern California
Breaking the Information Silo: Semantic Personas for Cross-Domain Recommendation
Jun 1, 2026Jonathan Mayo, Moshe Unger, Konstantin BaumanCross-Domain Transfer Learning Recommender Systems
Technology and Information Management Department, Coller School of Management, Tel Aviv University, Tel Aviv 6997801, Israel · Management Information Systems Department, Fox School of Business, Temple University, Philadelphia, Pennsylvania 19122
Time-Aware Diffusion based on Preference Disentanglement for Generative Recommendation
Jun 1, 2026Bangguo Zhu, Peng Huo, Yuanbo Zhao +3Sequential Recommendation Recommender Systems
Central South University Changsha, China · National Super Computing Center Tianjin, China · Renmin University of China Beijing, China +1
Large Language Models Should Learn Personalized Rather Than Aggregated Human Preferences
May 30, 2026Cristina GarbaceaLLM Alignment Social Choice Theory
University of Chicago, Data Science Institute, Chicago, USA.
CUPID in the Model Zoo: Online Matchmaking for Selecting Your Dream LLM
May 30, 2026Son Nguyen, Xinyuan Liu, Ransalu SenanayakeMulti-Armed Bandits User Preference Modeling
School of Computing and Augmented Intelligence, Arizona State University, Tempe, United States of America
Preference-Aware Rubric Learning for Personalized Evaluation
May 29, 2026Yilun Qiu, Xiaoyan Zhao, Yang Zhang +7LLM Evaluation LLM Alignment
National University of Singapore · Xiaohongshu Inc. · The University of Tokyo
Federated Variational Preference Alignment with Gumbel-Softmax Prior for Personalized User Preferences
May 29, 2026Jabin Koo, Hoyoung Kim, Minwoo Jang +1LLM Alignment Preference Alignment
Department of CSE, POSTECH, Pohang, Republic of Korea · National AI Research Lab, Seoul, Republic of Korea · Graduate School of AI, POSTECH, Pohang, Republic of Korea
Toward User Preference Alignment in LLM Recommendation via Explicit Context Feedback
May 27, 2026Weizhi Zhang, Wooseong Yang, Yuxin Cui +9Recommender Systems Large Language Model-Based Recommendation
University of Illinois Chicago, Chicago, USA · Meta, Menlo Park, USA
StoryLens: Preference-Aligned Story Rewriting via Context-Aware Narrative Enrichment
May 27, 2026Hanwen Cui, Yuting Mei, Yuhang Fu +2Reward Modeling Personalized Text Generation
Beijing University of Posts and Telecommunications · AIM3 Lab, Renmin University of China · Nanyang Technological University
VitaBench 2.0: Evaluating Personalized and Proactive Agents in Long-Term User Interactions
May 26, 2026Yuxin Chen, Yi Zhang, Zhengzhou Cai +11LLM Agent Memory AI Agent Evaluation
1National University of Singapore · 2Meituan · University of Science and Technology of China +2
L2Rec: Towards Dual-View Understanding of LLMs for Personalized Recommendation
May 26, 2026Pingjun Pan, Tingting Zhou, Peiyao Lu +3Mixture-of-Experts Language Models LLM Personalization
Netease Cloud Music Hangzhou, China
LATTE: Forecasting Peer Anchored Preference Trajectories for Personalized LLM Generation
May 26, 2026Jinze Li, Xiaoyan Yang, Shuo Yang +5LLM Personalization Personalized Language Models
The University of Hong Kong · Ant Healthcare, Ant Group
StreamProfileBench: A Benchmark for Fine-Grained User Profile Inference in Real-World Streaming Scenarios
May 25, 2026Sizhe Wang, Feiyu Duan, Juelin Wang +2LLM Evaluation User Modeling
School of Data Science, Fudan University · Shanghai University of Finance and Economics · Shanghai Innovation Institute +2
Selective Test-Time Compute Scaling for Click-Through Rate Prediction via Uncertainty-Triggered Feature Path Exploration
May 24, 2026Moyu Zhang, Yun Chen, Yujun Jin +3Cost-Aware Inference Test-Time Scaling
Alibaba Group Beijing, China
Self-Balancing Gradient Allocation for Heterogeneity-Aware Feature Generation in Click-Through Rate Prediction
May 24, 2026Moyu Zhang, Yun Chen, Yujun Jin +3Adaptive Loss Weighting CTR Prediction
Alibaba Group · Beijing, China
Ocean4Rec: Offline LLM-Derived OCEAN Profiles for Request-Time VOD Reranking
May 22, 2026Wonkyun Kim, Sehyun Bae, Kwanki Ahn +5Recommender Systems Large Language Model-Based Recommendation
Samsung Electronics Republic of Korea · Samsung Electronics India
Truthful Online Preference Aggregation for LLM Fine-Tuning in Mobile Crowdsourcing
May 22, 2026Shugang Hao, Lingjie DuanMechanism Design LLM Fine-Tuning
Singapore Wireless Innovation Centre, Singapore University of Technology and Design, Singapore, 487372 Singapore · Internet of Things Thrust and the Artificial Intelligence Thrust, Hong Kong University of Science and Technology, Guangzhou 511455, China
AttuneBench: A Conversation-Based Benchmark for LLM Emotional Intelligence
May 20, 2026Kate M. Lubrano, Faisal Sayed, Ankita Rathod +4LLM Evaluation Emotion Recognition in Conversations
1Pareto, California, US · 2Thoughtful, California, US · University of Pennsylvania, Pennsylvania, US
APM: Evaluating Style Personalization in LLMs with Arbitrary Preference Mappings
May 20, 2026Philipp Spohn, Leander Girrbach, Zeynep AkataLLM Evaluation LLM Personalization
Technical University of Munich, Helmholtz Munich · Munich Center for Machine Learning (MCML)
Spectral Souping: A Unified Framework for Online Preference Alignment
May 19, 2026Yinlam Chow, Guy Tennenholtz, Ted Yun +4Multi-Objective Language Model Alignment Preference Alignment
Google DeepMind · Google Research
From Volume to Value: Preference-Aligned Memory Construction for On-Device RAG
May 18, 2026Changmin Lee, Jaemin Kim, Taesik GongRetrieval-Augmented Generation Memory-Augmented Language Models
Department of Computer Science and Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.
Generative Long-term User Interest Modeling for Click-Through Rate Prediction
May 15, 2026Jiangli Shao, Kaifu Zheng, Hao Fang +5CTR Prediction User Modeling
MeiTuan Beijing, China
Agentic Recommender System with Hierarchical Belief-State Memory
May 14, 2026Xiang Shen, Yuhang Zhou, Yifan Wu +8LLM Agent Memory Recommender Systems
Meta Recommendation Systems (MRS)
Learning Transferable Latent User Preferences for Human-Aligned Decision Making
May 12, 2026Alina Hyk, Sandhya SaisubramanianLLM Alignment LLM Decision-Making
Oregon State University
Variance-aware Reward Modeling with Anchor Guidance
May 12, 2026Shuxing Fang, Ruijian Han, Liangyu Zhang +1Pairwise Preference Learning Reward Modeling
Department of Data Science and Artificial Intelligence, Hong Kong Polytechnic University · School of Statistics and Data Science, Shanghai University of Finance and Economics
When to Ask a Question: Understanding Communication Strategies in Generative AI Tools
May 11, 2026Charlotte Park, Kate Donahue, Manish RaghavanSocial Bias in Language Models Algorithmic Fairness
Massachusetts Institute of Technology Cambridge, Massachusetts, USA
Personalizing LLMs with Binary Feedback: A Preference-Corrected Optimization Framework
May 11, 2026Xilai Ma, Liye Zhao, Weijun Yao +3LLM Personalization User Preference Modeling
Harbin Institute of Technology, Shenzhen, China · Huawei Technologies Co., Ltd. · Nanyang Technological University
Personalized Alignment Revisited: The Necessity and Sufficiency of User Diversity
May 9, 2026Enoch Hyunwook KangLLM Alignment Personalized Language Model Alignment
Foster School of Business, University of Washington, Seattle, Washington, USA.

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Personalized Image Aesthetic Assessment via Preference-rich Sample Mining and Cohort Merging

Zhichao Yang, Tianjiao Gu, Zhixianhe Zhang, Xiangfei Sheng+2

Xidian University Xi’an, China · Xidian University Xian, China

Personalized Image Aesthetics Assessment Image Quality Assessment Model Merging User Preference Modeling

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Personalized Image Aesthetic Assessment (PIAA) aims to predict aesthetic ratings of images that vary across individuals. The aesthetic preferences manifest to different extents across distinct visual stimuli and exhibit cohort-specific patterns. Motivated by the above fact, this paper presents a Multimodal Large Language Model (MLLM)-based approach, which models individual aesthetic preferences by Preference-Rich sample mining and Aesthetically-resonant Cohort merging (PRAC). Specifically, PRAC first identifies preference-rich samples by analyzing both Collective Controversy and Personalized Deviation of images, maximizing the utility of limited user data. Based upon the preference-rich samples, cross-user preference similarities are measured by comparing preference embeddings. Then, a cohort-based model merging strategy, is proposed by aggregating preference patterns from aesthetically-resonant users, which further enhances the personalization for the target individual. Extensive experiments and comparisons on four benchmark PIAA databases demonstrate the superiority of the proposed PRAC model over the state-of-the-arts. The code and model will be public at https://github.com/yzc-ippl/PRAC.

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