mlsanityData to 14 Oct 2026

Personalization of Large Language Models: A Survey

arXiv 2411.00027 ↗First posted 29 Oct 2024cs.CLcited by 104

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Abstract (arXiv)

Personalization of Large Language Models (LLMs) has recently become increasingly important with a wide range of applications. Despite the importance and recent progress, most existing works on personalized LLMs have focused either entirely on (a) personalized text generation or (b) leveraging LLMs for personalization-related downstream applications, such as recommendation systems. In this work, we bridge the gap between these two separate main directions for the first time by introducing a taxonomy for personalized LLM usage and summarizing the key differences and challenges. We provide a formalization of the foundations of personalized LLMs that consolidates and expands notions of personalization of LLMs, defining and discussing novel facets of personalization, usage, and desiderata of personalized LLMs. We then unify the literature across these diverse fields and usage scenarios by proposing systematic taxonomies for the granularity of personalization, personalization techniques, datasets, evaluation methods, and applications of personalized LLMs. Finally, we highlight challenges and important open problems that remain to be addressed. By unifying and surveying recent research using the proposed taxonomies, we aim to provide a clear guide to the existing literature and different facets of personalization in LLMs, empowering both researchers and practitioners.

Key facts. Cited by 104 papers in the map (data through 14 Oct 2026). First posted on arXiv 29 Oct 2024.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 50; 2026: 54.

104 papers.

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  1. 2025A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligencecited by 170
  2. 2025In Prospect and Retrospect: Reflective Memory Management for Long-term Personalized Dialogue Agentscited by 106
  3. 2025PersonaMem-v2: Towards Personalized Intelligence via Learning Implicit User Personas and Agentic Memorycited by 88
  4. 2025A Survey of Personalized Large Language Models: Progress and Future Directionscited by 71
  5. 2025FalseReject: A Resource for Improving Contextual Safety and Mitigating Over-Refusals in LLMs via Structured Reasoningcited by 58
  6. 2025Measuring What Makes You Unique: Difference-Aware User Modeling for Enhancing LLM Personalizationcited by 45
  7. 2026Doc-to-LoRA: Learning to Instantly Internalize Contextscited by 43
  8. 2025Personalized Text Generation with Contrastive Activation Steeringcited by 34
  9. 2025Language Model Personalization via Reward Factorizationcited by 31
  10. 2026TiMem: Temporal-Hierarchical Memory Consolidation for Long-Horizon Conversational Agentscited by 31
  11. 2025A Survey on Personalized and Pluralistic Preference Alignment in Large Language Modelscited by 27
  12. 2025Teaching Language Models to Evolve with Users: Dynamic Profile Modeling for Personalized Alignmentcited by 24
38 more
  1. 2025Open Character Training: Shaping the Persona of AI Assistants through Constitutional AIcited by 24
  2. 2025Representation Engineering for Large-Language Models: Survey and Research Challengescited by 21
  3. 2025Whose Boat Does it Float? Improving Personalization in Preference Tuning via Inferred User Personascited by 19
  4. 2025CiteEval: Principle-Driven Citation Evaluation for Source Attributioncited by 19
  5. 2025A Personalized Conversational Benchmark: Towards Simulating Personalized Conversationscited by 17
  6. 2025Evaluating Long-Context Reasoning in LLM-Based WebAgentscited by 15
  7. 2026Skill-R1: Agent Skill Evolution via Reinforcement Learningcited by 15
  8. 2025Epistemic Alignment: A Mediating Framework for User-LLM Knowledge Deliverycited by 14
  9. 2025The Era of Real-World Human Interaction: RL from User Conversationscited by 13
  10. 2026VitaBench 2.0: Evaluating Personalized and Proactive Agents in Long-Term User Interactionscited by 12
  11. 2026PersonaVLM: Long-Term Personalized Multimodal LLMscited by 11
  12. 2025Rethinking Diverse Human Preference Learning through Principal Component Analysiscited by 10
  13. 2025In-context Ranking Preference Optimizationcited by 9
  14. 2025AdaBoN: Adaptive Best-of-N Alignmentcited by 9
  15. 2025No for Some, Yes for Others: Persona Prompts and Other Sources of False Refusal in Language Modelscited by 9
  16. 2025Personalization Toolkit: Training Free Personalization of Large Vision Language Modelscited by 8
  17. 2025Capturing Individual Human Preferences with Reward Featurescited by 8
  18. 2025Advancing and Benchmarking Personalized Tool Invocation for LLMscited by 8
  19. 2025Generative AI for Autonomous Driving: Frontiers and Opportunitiescited by 7
  20. 2025T-POP: Test-Time Personalization with Online Preference Feedbackcited by 7
  21. 2026User as Code: Executable Memory for Personalized Agentscited by 7
  22. 2025ToolSpectrum : Towards Personalized Tool Utilization for Large Language Modelscited by 6
  23. 2025Beyond Data Privacy: New Privacy Risks for Large Language Modelscited by 6
  24. 2025Dissecting Persona-Driven Reasoning in Language Models via Activation Patchingcited by 5
  25. 2025PREF: Reference-Free Evaluation of Personalised Text Generation in LLMscited by 5
  26. 2025Counterfactual Reasoning for Steerable Pluralistic Value Alignment of Large Language Modelscited by 5
  27. 2026Long Context, Less Focus: A Scaling Gap in LLMs Revealed through Privacy and Personalizationcited by 5
  28. 2026Personalization Increases Affective Alignment but Has Role-Dependent Effects on Epistemic Independence in LLMscited by 5
  29. 2026ComBodied Agents: a New Paradigm of Human-Centric Agentic AIcited by 5
  30. 2025Reasoning Meets Personalization: Unleashing the Potential of Large Reasoning Model for Personalized Generationcited by 4
  31. 2025RPM: Reasoning-Level Personalization for Black-Box Large Language Modelscited by 3
  32. 2026Rethinking Personalization in Large Language Models at the Token Levelcited by 3
  33. 2026GISTBench: Evaluating LLM User Understanding via Evidence-Based Interest Verificationcited by 3
  34. 2026Ads in AI Chatbots? An Analysis of How Large Language Models Navigate Conflicts of Interestcited by 3
  35. 2026Personal Visual Context Learning in Large Multimodal Modelscited by 3
  36. 2025UC-MOA: Utility-Conditioned Multi-Objective Alignment for Distributional Pareto-Optimalitycited by 2
  37. 2025PersonaBOT: Bringing Customer Personas to Life with LLMs and RAGcited by 2
  38. 2025Aligning VLM Assistants with Personalized Situated Cognitioncited by 2

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