mlsanityData to 7 Oct 2026

Measuring What Makes You Unique: Difference-Aware User Modeling for Enhancing LLM Personalization

arXiv 2503.02450 ↗First posted 4 Mar 2025cs.CLcited by 44

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Abstract (arXiv)

Personalizing Large Language Models (LLMs) has become a critical step in facilitating their widespread application to enhance individual life experiences. In pursuit of personalization, distilling key preference information from an individual's historical data as instructional preference context to customize LLM generation has emerged as a promising direction. However, these methods face a fundamental limitation by overlooking the inter-user comparative analysis, which is essential for identifying the inter-user differences that truly shape preferences. To address this limitation, we propose Difference-aware Personalization Learning (DPL), a novel approach that emphasizes extracting inter-user differences to enhance LLM personalization. DPL strategically selects representative users for comparison and establishes a structured standard to extract meaningful, task-relevant differences for customizing LLM generation. Extensive experiments on real-world datasets demonstrate that DPL significantly enhances LLM personalization. We release our code at https://github.com/SnowCharmQ/DPL.

Key facts. Cited by 44 papers in the map (data through 7 Oct 2026). Builds on 43 of its 84 references that are in the map. First posted on arXiv 4 Mar 2025.

Builds on

43 of 84 references.

References · 43

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2024The Llama 3 Herd of Modelscited by 14,192
  3. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  4. 2023Efficient Memory Management for Large Language Model Serving with PagedAttentioncited by 5,767
  5. 2023G-Eval: NLG Evaluation using GPT-4 with Better Human Alignmentcited by 2,205
  6. 2018A Call for Clarity in Reporting BLEU Scorescited by 1,790
  7. 2023Towards General Text Embeddings with Multi-stage Contrastive Learningcited by 705
  8. 2024LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memorycited by 656
  9. 2024A Survey on the Memory Mechanism of Large Language Model based Agentscited by 622
  10. 2023LaMP: When Large Language Models Meet Personalizationcited by 425
  11. 2023TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendationcited by 336
  12. 2024Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Securitycited by 257
31 more
  1. 2024AlphaEdit: Null-Space Constrained Knowledge Editing for Language Modelscited by 224
  2. 2024Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoderscited by 213
  3. 2025Do LLMs Recognize Your Preferences? Evaluating Personalized Preference Following in LLMscited by 142
  4. 2024Hello Again! LLM-powered Personalized Agent for Long-term Dialoguecited by 121
  5. 2023Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Predictioncited by 113
  6. 2023GPT4Rec: A Generative Framework for Personalized Recommendation and User Interests Interpretationcited by 101
  7. 2024Personalization of Large Language Models: A Surveycited by 100
  8. 2023CoLLM: Integrating Collaborative Embeddings into Large Language Models for Recommendationcited by 99
  9. 2024Optimization Methods for Personalizing Large Language Models through Retrieval Augmentationcited by 98
  10. 2023Pearl: Personalizing Large Language Model Writing Assistants with Generation-Calibrated Retrieverscited by 91
  11. 2024LongLaMP: A Benchmark for Personalized Long-form Text Generationcited by 91
  12. 2024On Softmax Direct Preference Optimization for Recommendationcited by 64
  13. 2024Large Language Models Empowered Personalized Web Agentscited by 64
  14. 2024HYDRA: Model Factorization Framework for Black-Box LLM Personalizationcited by 59
  15. 2024PAD: Personalized Alignment of LLMs at Decoding-Timecited by 58
  16. 2023Teach LLMs to Personalize -- An Approach inspired by Writing Educationcited by 48
  17. 2024Persona-DB: Efficient Large Language Model Personalization for Response Prediction with Collaborative Data Refinementcited by 47
  18. 2024On the Multi-turn Instruction Following for Conversational Web Agentscited by 42
  19. 2023SentimentGPT: Exploiting GPT for Advanced Sentiment Analysis and its Departure from Current Machine Learningcited by 38
  20. 2024Harnessing Large Language Models for Text-Rich Sequential Recommendationcited by 38
  21. 2024Leveraging Large Language Models for NLG Evaluation: Advances and Challengescited by 37
  22. 2025Reasoning-Enhanced Self-Training for Long-Form Personalized Text Generationcited by 26
  23. 2022How Far are We from Robust Long Abstractive Summarization?cited by 25
  24. 2024Text-like Encoding of Collaborative Information in Large Language Models for Recommendationcited by 25
  25. 2023Large Language Models for User Interest Journeyscited by 24
  26. 2025Beware of Your Po! Measuring and Mitigating AI Safety Risks in Role-Play Fine-Tuning of LLMscited by 22
  27. 2024Customizing Language Model Responses with Contrastive In-Context Learningcited by 19
  28. 2025Self-Improvement Towards Pareto Optimality: Mitigating Preference Conflicts in Multi-Objective Alignmentcited by 15
  29. 2024Review-LLM: Harnessing Large Language Models for Personalized Review Generationcited by 14
  30. 2019A Lexical, Syntactic, and Semantic Perspective for Understanding Style in Textcited by 8
  31. 2024Leveraging Memory Retrieval to Enhance LLM-based Generative Recommendationcited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 16; 2026: 28.

44 papers.

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  1. 2025O-Mem: Omni Memory System for Personalized, Long Horizon, Self-Evolving Agentscited by 30
  2. 2025Think-While-Generating: On-the-Fly Reasoning for Personalized Long-Form Generationcited by 29
  3. 2025Teaching Language Models to Evolve with Users: Dynamic Profile Modeling for Personalized Alignmentcited by 22
  4. 2025Latent Inter-User Difference Modeling for LLM Personalizationcited by 20
  5. 2025L-MTP: Leap Multi-Token Prediction Beyond Adjacent Context for Large Language Modelscited by 14
  6. 2025Anthropomimetic Uncertainty: What Verbalized Uncertainty in Language Models is Missingcited by 14
  7. 2025Persona-judge: Personalized Alignment of Large Language Models via Token-level Self-judgmentcited by 11
  8. 2025TOM-SWE: User Mental Modeling For Software Engineering Agentscited by 11
  9. 2026Toward Personalized LLM-Powered Agents: Foundations, Evaluation, and Future Directionscited by 10
  10. 2025MemWeaver: A Hierarchical Memory from Textual Interactive Behaviors for Personalized Generationcited by 8
  11. 2025SteerX: Disentangled Steering for LLM Personalizationcited by 7
  12. 2026AlpsBench: An LLM Personalization Benchmark for Real-Dialogue Memorization and Preference Alignmentcited by 6
32 more
  1. 2025POPI: Personalizing LLMs via Optimized Natural Language Preference Inferencecited by 5
  2. 2026PERM: Psychology-grounded Empathetic Reward Modeling for Large Language Modelscited by 5
  3. 2025Reinforced Strategy Optimization for Conversational Recommender Systems via Network-of-Expertscited by 4
  4. 2025Tagging the Thought: Unlocking Personalization Reasoning via Reinforcement Learningcited by 3
  5. 2026Know You Before You Speak: User-State Modeling for LLM Personalization in Multi-Turn Conversationcited by 3
  6. 2025Mnemosyne: An Unsupervised, Human-Inspired Long-Term Memory Architecture for Edge-Based LLMscited by 2
  7. 2026CARD: Cluster-level Adaptation with Reward-guided Decoding for Personalized Text Generationcited by 2
  8. 2026When Personalization Misleads: Understanding and Mitigating Hallucinations in Personalized LLMscited by 2
  9. 2026Meet Dynamic Individual Preferences: Resolving Conflicting Human Value with Paired Fine-Tuningcited by 2
  10. 2026Preference Heads in Large Language Models: A Mechanistic Framework for Interpretable Personalizationcited by 2
  11. 2026Preference-Aware Rubric Learning for Personalized Evaluationcited by 2
  12. 2026TSUBASA: Improving Long-Horizon Personalization via Evolving Memory and Self-Learning with Context Distillationcited by 1
  13. 2026LATTE: Forecasting Peer Anchored Preference Trajectories for Personalized LLM Generationcited by 1
  14. 2026Towards Root Memories: Benchmarking and Enhancing Implicit Logical Memory Retrieval for Personalized LLMscited by 1
  15. 2025Explain Less, Understand More: Data-Efficient Personalization of Reader-Dependent Jargonscited by 0
  16. 2025Comparative Personalization for Multi-document Summarizationcited by 0
  17. 2026Do Implicit Personalization and Explicit Styles Conflict? PsPLUG: A Lightweight Plug-in for Balancing Personalization and Style in Customized LLMscited by 0
  18. 2026The Subjectivity of Respect in Police Traffic Stops: Modeling Community Perspectives in Body-Worn Camera Footagecited by 0
  19. 2026NextAds: Towards Next-generation Personalized Video Advertisingcited by 0
  20. 2026Recall Isn't Enough: Bounding Commitments in Personalized Language Systemscited by 0
  21. 2026StreamProfileBench: A Benchmark for Fine-Grained User Profile Inference in Real-World Streaming Scenarioscited by 0
  22. 2026ChildEval: When large language models meet children's personalitiescited by 0
  23. 2026PAFO: Pareto Fairness Optimization for Personalized Reward Modelingcited by 0
  24. 2026The Personalization Mirage: How LLMs Fabricate User Profiles, and Why Self-Monitoring Misleadscited by 0
  25. 2026PersonaEdit: Representative Sample Selection for Personalized Model Editingcited by 0
  26. 2026VIBE-Bench: Evaluating Personalized Large Language Models When Profiles Don't Mean Preferencescited by 0
  27. 2026PLUME: Parameter-Efficient Personalization of Large Language Models via Low-Rank User Modulation in Shared Subspacescited by 0
  28. 2026HyperTrace: Hypothesis-Based Preference Tracing for Online LLM Personalizationcited by 0
  29. 2026COPE: Continual Personalization of LLMs under Sparse User Feedback via User Embeddings and Self-Evaluationcited by 0
  30. 2026Beyond End-to-End Black Box Mapping: An Intentional Agent Framework for Cognitive-driven Facial Reaction Generationcited by 0
  31. 2026Rubric-Aware On-Policy Self-Distillation for LLM Personalizationcited by 0
  32. 2026Gradient-Aligned Pair Selection for Personalized Preference Optimizationcited by 0