LLM Personalization

LLM: Large Language Model

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10 papers in the last four weeks, up 25% on the four weeks before. 0.1% of all new papers.

Jul 13Week of Sep 28

Latest papers 104

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Personal-Agent Mediated Recommendation with Cross-Platform User History
Oct 6, 2026Yu Xia, Jiangfan Zhang, Jun Xiao +2LLM Personalization Recommender Systems
University of California San Diego · Meta · Meta AI
Rubric-Aware On-Policy Self-Distillation for LLM Personalization
Sep 28, 2026Yilun Qiu, Xiaoyan Zhao, Chengbing Wang +6LLM Personalization On-Policy Self-Distillation
Xiaohongshu Inc. · National University of Singapore · University of Science and Technology of China +1
Memory Has Geometry: Non-Uniform Geometric Memory for Long-Horizon Personalized AI
Sep 16, 2026Jiahong Liu, Wenhao Yu, Zexuan Qiu +2Neural Representation Geometry LLM Personalization
The Chinese University of Hong Kong, Hong Kong SAR, China · The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China
Mind2Dialogue: Training Human-Aware Language Models by Simulating User Mental States
Sep 14, 2026Zixuan Wang, Yufan Zhou, Jinzhou Tang +16LLM Personalization Theory of Mind
UC San Diego · KU Leuven · Johns Hopkins University +2
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 Models LLM Personalization
Baidu Inc., Beijing, China
Creating an Atomic User Model for Personality-Aware Large Language Model Interaction
Sep 10, 2026B. Sankar, Deepthika S, Pawni Yadav +1LLM Personalization Personality Modeling in Language Models
Department of Mechanical Engineering, Indian Institute of Science (IISc), Bengaluru, 560012, Karnataka, India · Department of Design and Manufacturing, Indian Institute of Science (IISc), Bengaluru, 560012, Karnataka, India
HyperTrace: Hypothesis-Based Preference Tracing for Online LLM Personalization
Sep 9, 2026Jianzhi Shen, Keyu Mao, Minghao Shao +7LLM Personalization Personalized Language Models
Johns Hopkins University · Institute of Science Tokyo · NYU Tandon +1
Less Is Personal: Learning Minimal Sufficient User Profiles for Personalized Language Models
Sep 8, 2026Minghang Liu, Qiang Qiu, Yuanzhuo Wang +2LLM Personalization Memory-Augmented Language Models
State Key Laboratory of AI Safety, Institute of Computing Technology, CAS · University of Chinese Academy of Sciences, Beijing, China
Aegix Pulse: A Traceable Three-Stage Architecture for Personalized Content Generation and Context-Preserving Revision
Sep 7, 2026Hongnan Zhao, Shiyu Chen, Zhihao ChenLLM Personalization Evidence-Grounded Generation
1Aegix Insight
PLUME: Parameter-Efficient Personalization of Large Language Models via Low-Rank User Modulation in Shared Subspaces
Sep 7, 2026Xinyu Li, Hao Zhou, Jianfeng Zhu +4LLM Personalization Low-Rank Adaptation
Department of Computer Science Kent State University Kent, OH 44242, USA
Aplaud: Adaptive Personalized Low-Rank Decomposition for User-Specific LLM
Sep 7, 2026Xinyu Li, Ruoming Jin, Jianfeng Zhu +2LLM Personalization Low-Rank Adaptation
Department of Computer Science, Kent State University · iLambda Inc.
A Prompt-Engineering Approach to Develop Scalable, Flexible, and Real-Time Hybrid Micro-Level Personalization in a General Purpose AI Teaching Assistant
Sep 3, 2026Saptarshi Basu, Sandeep Kakar, Ashok GoelLLM Personalization Intelligent Tutoring Systems
Georgia Institute of Technology, Atlanta GA 30332, USA
VIBE-Bench: Evaluating Personalized Large Language Models When Profiles Don't Mean Preferences
Sep 1, 2026Yiwen Jiang, Yang Deng, Stephanie Fong +9LLM Evaluation LLM Personalization
1Monash University · 2Singapore Management University · University of Liverpool +1
Hypotheses-Guided Self Distillation for Continual Personalization
Aug 31, 2026EunJeong Hwang, Kushan Mitra, Dan Zhang +2Continual Learning for LLMs LLM Personalization
University of British Columbia · Work done as an intern at Megagon Labs. · Megagon Labs, USA
Locating and Controlling Implicit Personalization in Large Language Models
Aug 12, 2026Yueru Yan, Siqi Wu, Thai LeLLM Personalization LLM Interpretability
Indiana University Bloomington, USA
Weightless Fine-Tuning: Personalizing LLMs via Logit-Space Transport
Aug 11, 2026Bohan Zhang, Anqi Ni, Yixin Wang +1Supervised Fine-Tuning LLM Personalization
University of Michigan · University of Chicago
Do Personalized Skills Help Coding Agents? An Empirical Study of Developer Interaction Histories
Aug 10, 2026Shuyan Huang, Kai Du, Andrew LanLLM Personalization Coding Agents
UMass Amherst
Learning Preference Adaptation for Large Language Model Personalization via Verbal Reinforcement Learning
Aug 10, 2026Yuting Liu, Wei Wu, Jianzhe Zhao +1LLM Personalization Meta-Learning
Software College, Northeastern University, China · Ant International
UserToolBench: A User-Profile-Hidden Benchmark for Personalized Decision Making in Tool-Use LLMs
Aug 10, 2026Xuexiong Yin, Zechuan Chen, Yongsen Zheng +5Tool-Use Evaluation Tool-Augmented Language Model Agents
Sun Yat-Sen University · Nanyang Technological University · Huawei Noah’s Ark Lab
TRACE-Memory: Public-Conditioned Retrieval and Utility-Aware Evidence Admission for Personalized Generation
Aug 9, 2026Jing Wang, Zhu Wang, Yifan Guo +2Retrieval-Augmented Generation LLM Personalization
Northwest Polytechnical University
Cautious Context Steering for Language Model Personalization
Aug 6, 2026Gihoon Kim, Jeyoung Lee, Suhan Woo +4Language Model Steering LLM Personalization
Yonsei University · Hyundai Motors Company · Korea Institute of Science and Technology
LUNAR: Benchmarking Personalized Large Language Models on UNiversal User BehAvioR Logs
Aug 5, 2026Jiahao Zhang, Yongzhi Tong, Zelin Fu +4LLM Evaluation LLM Personalization
1Shenzhen University of Advanced Technology · ♣Work done at Ant Group · 2Ant Group +1
The Personalization Mirage: How LLMs Fabricate User Profiles, and Why Self-Monitoring Misleads
Aug 5, 2026Yushi Sun, Yanjie Zhang, Rui ShengLLM Evaluation LLM Personalization
LIGHTSPEED, Shenzhen, China · The Hong Kong University of Science and Technology, Hong Kong, China · Tencent LIGHTSPEED
From Profiling to Synthesis: Benchmarking Implicit Behavioral Alignment in Personalized LLM Agents
Aug 3, 2026Jiajia Song, Bobo Li, Haiwen Yi +6LLM Personalization LLM Agent Evaluation
National University of Singapore · University of Toronto · University of Minnesota Twin Cities +2
PGMem: Tightly Coupled Persona-Memory Graph for Lifelong Personalized Agents
Aug 3, 2026Wonjun Choi, Yerim Kim, Yukyung Lee +1Agent Memory LLM Personalization
Korea University, Seoul, Korea · Boston University, Boston, USA
Learning to Adapt Cross-Domain Preferences via Meta-LoRA for LLM Personalization
Aug 1, 2026Xuefei Wang, Jun Han, Zixuan Wang +4Few-Shot Domain Adaptation LLM Personalization
Beihang University · Nankai University
Personalizing Large Language Model Agents with Small Policy Models
Jul 31, 2026Dian Jin, Zhi Zhang, Huichao Li +3LLM Personalization LLM Agents
Department of Statistics and Data Science, National University of Singapore · Department of Statistics and Data Science, University of California, Los Angeles · Department of Data Science, Fudan University
Know It, Act on It: Investigating Memory Utilization in LLM Personalization
Jul 31, 2026Zhaoxin Feng, Jianfei Ma, Emmanuele ChersoniLLM Personalization LLM Agent Memory
The Hong Kong Polytechnic University
Learning Dynamic User Personas from Implicit Interaction Streams via Iterative Refinement
Jul 29, 2026Haifeng WuLLM Personalization User Modeling
PayPal
Mi-Memory: A Lifecycle Memory Framework for Personal AI
Jul 21, 2026Xule Liu, Hanlin Teng, Chao Li +15Multimodal Memory LLM Personalization
Darwin Agent Team

Oct 6, 2026, cs.AIJ/K move · Enter open · S save

Personal-Agent Mediated Recommendation with Cross-Platform User History

Yu Xia, Jiangfan Zhang, Jun Xiao, Julian McAuley+1

University of California San Diego · Meta · Meta AI

LLM Personalization Recommender Systems Large Language Model-Based Recommendation

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Modern recommendation is shifting from platform-centric personalization toward user-governed personalization, where a personal LLM agent can act on the user's behalf across services. We formalize this emerging paradigm as Personal-Agent Mediated Recommendation: a platform recommender ranks a candidate set using platform-local information, and a personal agent uses user-authorized cross-platform history to mediate the resulting ranking and produce the final top-K slate. Such mediation is nontrivial: the platform ranking can encode strong population evidence that the personal agent cannot observe, so effective mediation must therefore balance beneficial rescues against harmful overrides. To study this trade-off, we introduce MediateRec, a benchmark that includes scalable proxy cross-platform environments and a real cross-platform test under a controlled platform-agent information boundary. To train the agent to use cross-platform history effectively, we further propose Personal Attribution Mediation Optimization (PAMO), which counterfactually masks that history to estimate personal mediation support and reallocates rank-aware advantage mass under a platform-relative value floor. We theoretically prove that PAMO preserves cutoff-level advantage mass and is locally optimal among first-order reallocations that preserve this mass without lowering average platform-relative value. Experiments on MediateRec show that personal-agent mediation enables meaningful platform corrections, yet even strong proprietary LLMs introduce non-negligible harmful overrides. PAMO consistently improves over matched outcome-only RL across seen and unseen target platforms and on the real cross-platform test, while achieving a better rescue-harm balance.

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Latest papers 104