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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Persona Conditioning of Brand Recommendations in Retrieval-Augmented Commercial Chat: A Prominence-Stratified Cross-Provider Audit
May 28, 2026Will Jack, Noah Lehman, Keller Maloney +1LLM Personalization Recommender Systems
Unusual
Personalized Turn-Level User Conversation Satisfaction Benchmark
May 28, 2026Zhefan Wang, Zhiqiang Guo, Weizhi Ma +3Human Preference Evaluation LLM Personalization
Department of Computer Science and Technology, Tsinghua University, Beijing, China. · Institute for AI Industry Research, Tsinghua University, Beijing, China. · Meituan.
Beyond Recall: Behavioral Specification as an Interpretive Layer for AI Personalization
May 27, 2026Aarik GulayaLLM Personalization AI Alignment
Base Layer
ChildEval: When large language models meet children's personalities
May 27, 2026Yanyan Luo, Xue Han, Chunxu Zhao +5LLM Evaluation LLM Personalization
JIUTIAN Research, China Mobile, Beijing, China
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
Beyond Inference-Only Deployment: Comparing Weight-Based Consolidation Against Cascading Compaction
May 23, 2026Simon Dennis, Kevin Shabahang, Hao Guo +1Continual Learning for LLMs LLM Personalization
i14 / University of Melbourne · i14
Know You Before You Speak: User-State Modeling for LLM Personalization in Multi-Turn Conversation
May 23, 2026Jiani Luo, Xiaoyan Zhao, Yang Zhang +4LLM Personalization User Modeling
School of Computing, National University of Singapore, Singapore · School of Artificial Intelligence, Beihang University, Beijing, China · Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China +1
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)
ThoughtTrace: Understanding User Thoughts in Real-World LLM Interactions
May 19, 2026Chuanyang Jin, Binze Li, Haopeng Xie +6LLM Personalization Human-AI Interaction
Johns Hopkins University · Massachusetts Institute of Technology · Google Research
Evaluating the Utility of Personal Health Records in Personalized Health AI
May 18, 2026Rory Sayres, Kejia Chen, Ayush Jain +19LLM Personalization Healthcare
1Google Research · †Work done while at Google Research
SimPersona: Learning Discrete Buyer Personas from Raw Clickstreams for Grounded E-Commerce Agents
May 14, 2026Zahra Zanjani Foumani, Alberto Castelo, Shuang Xie +3LLM Personalization Vector-Quantized Variational Autoencoder
Shopify · Bellevue, Washington, USA
PRISM-X: Experiments on Personalised Fine-Tuning with Human and Simulated Users
May 13, 2026Hannah Rose Kirk, Liu Leqi, Fanzhi Zeng +4LLM Evaluation LLM Sycophancy
University of Oxford · UK AI Security Institute · University of Texas at Austin +2
Training LLMs with Reinforcement Learning for Intent-Aware Personalized Question Answering
May 12, 2026Maryam Amirizaniani, Benjamin Charles Germain Lee, Jevin West +1RL for Language Models LLM Personalization
University of Washington, Seattle, WA, USA
An Annotation Scheme and Classifier for Personal Facts in Dialogue
May 11, 2026Konstantin ZaitsevLLM Personalization Text Classification
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
Test-Time Personalization: A Diagnostic Framework and Probabilistic Fix for Scaling Failures
May 9, 2026Linhai Zhang, Yulan HeReward Modeling Reward Hacking
King’s College London · The Alan Turing Institute
UserGPT Technical Report
May 9, 2026Yunyi Xuan, Hao Yi, Fengling Mao +9LLM Personalization User Modeling
1Alibaba Group
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
Taklif.AI: LLM-Powered Platform for Interest-Based Personalized College Assignments
May 7, 2026Zaki Kurdya, Mohammed Zuqlam, Salem Amassi +2LLM Personalization Generative AI in Education
Faculty of Information Technology The Islamic University of Gaza Gaza, Palestine
ExPerT: Personalizing LLM Responses to Users' Domain Expertise via Query-Wise Semantic and Keystroke Behavioral Cues
May 4, 2026Yeji Park, Jiwon Tark, Taesik GongLLM Personalization User Modeling
UNIST · Korea University
ReLay: Personalized LLM-Generated Plain-Language Summaries for Better Understanding, but at What Cost?
May 1, 2026Joey Chan, Yikun Han, Jingyuan Chen +8LLM Personalization Language Model Safety Evaluation
University of Illinois Urbana-Champaign · University of Virginia · University of Colorado Anschutz +4
Theory-Grounded Evaluation Exposes the Authorship Gap in LLM Personalization
Apr 29, 2026Yash Ganpat SawantLLM Evaluation LLM Personalization
Independent AI Researcher
MEMOR-E: In-Context and Fine-Tuned LLM Personalization for Alzheimer's Assistive Robotics
Apr 28, 2026Maissa Abir Smaili, Eren Sadikoglu, Ransalu SenanayakeAlzheimer's Disease LLM Personalization
Istanbul Medipol University Istanbul, Türkiye · Arizona State University Tempe, USA
Sparse Personalized Text Generation with Multi-Trajectory Reasoning
Apr 27, 2026Bo Ni, Haowei Fu, Qinwen Ge +10LLM Personalization Personalized Text Generation
Department of Computer Science, Vanderbilt University, Nashville, Tennessee · Adobe Research, San Jose, California · University of Orgeon, Eugene, Oregon
Preference Heads in Large Language Models: A Mechanistic Framework for Interpretable Personalization
Apr 24, 2026Weixu Zhang, Ye Yuan, Changjiang Han +7LLM Alignment Language Model Steering
McGill University · Mila - Quebec AI Institute · MBZUAI +2
Separable Expert Architecture: Toward Privacy-Preserving LLM Personalization via Composable Adapters and Deletable User Proxies
Apr 23, 2026Chris Schneider, Philipp Schoenegger, Ben BariachLLM Personalization Privacy-Preserving Language Models
Microsoft AI
JudgeMeNot: Personalizing Large Language Models to Emulate Judicial Reasoning in Hebrew
Apr 20, 2026Itay Razumenko, Arnon Sturm, Nir GrinbergLegal NLP LLM Personalization
Computer and Information Science Ben-Gurion University of the Negev Beer-Sheva, Israel
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
Enhancing Zero-shot Personalized Image Aesthetics Assessment with Profile-aware Multimodal LLM
Apr 19, 2026Chun Wang, Chenfeng Wei, Chenyang Liu +1Zero-Shot Learning Personalized Image Aesthetics Assessment
Mashang Consumer Finance Co., Ltd., Chongqing, China · Xi’an Jiaotong-Liverpool University, Suzhou, China · Beijing University of Posts and Telecommunications, Beijing, China

May 28, 2026, cs.AIJ/K move · Enter open · S save

Persona Conditioning of Brand Recommendations in Retrieval-Augmented Commercial Chat: A Prominence-Stratified Cross-Provider Audit

Will Jack, Noah Lehman, Keller Maloney, Sarah Xu

Unusual

LLM Personalization Recommender Systems Large Language Model-Based Recommendation Persona Prompting Persona-Conditioned Generation

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The same prompt -- "best CRM software" -- reaches AI assistants from buyers in widely different contexts: a solo founder, an enterprise VP, a UK SMB owner. We audit how strongly that contextual variation reshapes which brands the model recommends. The audit samples 2,000 runs over a design space of 10 personas x 8 prompts x 3 model configurations x N=10 reps, with the two OpenAI cells at full 8-prompt coverage and the Anthropic sonnet-4.6 / low cell at 4-prompt coverage. Prefixing the user message with a persona drops the recommendation-set similarity (Jaccard) by Delta = -0.12 to -0.20 relative to a same-persona baseline (clustered 95% CIs exclude zero on all three measured cells; the sonnet cell's CI rests on only 4 prompt clusters and is correspondingly wider). The effect is sharply prominence-stratified: category leaders are persona-resistant (~80% same-brand consistency across personas), but mid-market brands swap up to 75% of the recommendation set as the persona changes. The Anthropic model shows a larger point-estimate effect than the OpenAI configurations, though clustered CIs overlap for the closer contrast (sonnet vs. OpenAI/high); the asymmetry is consistent with Anthropic's more retrieval-unattributed generation route (43-52% recommendations without observed retrieval-layer evidence, vs OpenAI's 8-29%, documented in Jack 2026). Any measurement of AI brand perception must condition on the buyer persona supplying the query: the same prompt produces materially different recommendation sets depending on who the model thinks is asking, and a measurement protocol that aggregates across personas systematically obscures that variation. The effect concentrates at mid-market and is largest on the most priors-reliant generation route in our audit, consistent with persona responsiveness growing as models lean more on training-data priors and richer context integration.

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