mlsanityData to 14 Oct 2026

Personalized Pieces: Efficient Personalized Large Language Models through Collaborative Efforts

arXiv 2406.10471 ↗First posted 15 Jun 2024cs.CLcited by 74

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Abstract (arXiv)

Personalized large language models (LLMs) aim to tailor interactions, content, and recommendations to individual user preferences. While parameter-efficient fine-tuning (PEFT) methods excel in performance and generalization, they are costly and limit communal benefits when used individually. To this end, we introduce Personalized Pieces (Per-Pcs), a framework that allows users to safely share and assemble personalized PEFT efficiently with collaborative efforts. Per-Pcs involves selecting sharers, breaking their PEFT into pieces, and training gates for each piece. These pieces are added to a pool, from which target users can select and assemble personalized PEFT using their history data. This approach preserves privacy and enables fine-grained user modeling without excessive storage and computation demands. Experimental results show Per-Pcs outperforms non-personalized and PEFT retrieval baselines, offering performance comparable to OPPU with significantly lower resource use across six tasks. Further analysis highlights Per-Pcs's robustness concerning sharer count and selection strategy, pieces sharing ratio, and scalability in computation time and storage space. Per-Pcs's modularity promotes safe sharing, making LLM personalization more efficient, effective, and widely accessible through collaborative efforts.

Key facts. Cited by 74 papers in the map (data through 14 Oct 2026). Builds on 45 of its 68 references that are in the map. First posted on arXiv 15 Jun 2024.

Builds on

45 of 68 references.

References · 45

  1. 2017Attention Is All You Needcited by 60,361
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  3. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  4. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 13,028
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  6. 2021Prefix-Tuning: Optimizing Continuous Prompts for Generationcited by 3,915
  7. 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,780
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  9. 2022Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference timecited by 1,396
  10. 2021DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharingcited by 1,254
  11. 2022Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learningcited by 896
  12. 2021Towards a Unified View of Parameter-Efficient Transfer Learningcited by 872
33 more
  1. 2023Large Language Models Can Be Easily Distracted by Irrelevant Contextcited by 841
  2. 2023LaMP: When Large Language Models Meet Personalizationcited by 437
  3. 2022Dataless Knowledge Fusion by Merging Weights of Language Modelscited by 387
  4. 2023LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Compositioncited by 364
  5. 2023Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Mergingcited by 280
  6. 2023Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender Systemcited by 242
  7. 2023ZipLoRA: Any Subject in Any Style by Effectively Merging LoRAscited by 194
  8. 2022Branch-Train-Merge: Embarrassingly Parallel Training of Expert Language Modelscited by 191
  9. 2023Uncovering ChatGPT's Capabilities in Recommender Systemscited by 161
  10. 2023Text Is All You Need: Learning Language Representations for Sequential Recommendationcited by 149
  11. 2024Towards Safer Large Language Models through Machine Unlearningcited by 139
  12. 2024Personalized Language Modeling from Personalized Human Feedbackcited by 132
  13. 2023Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Predictioncited by 116
  14. 2022Fusing finetuned models for better pretrainingcited by 110
  15. 2023Are Emergent Abilities in Large Language Models just In-Context Learning?cited by 109
  16. 2023Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuningcited by 106
  17. 2024Optimization Methods for Personalizing Large Language Models through Retrieval Augmentationcited by 99
  18. 2022Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalizationcited by 97
  19. 2023Pearl: Personalizing Large Language Model Writing Assistants with Generation-Calibrated Retrieverscited by 92
  20. 2024Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuningcited by 90
  21. 2024Aligning to Thousands of Preferences via System Message Generalizationcited by 84
  22. 2023Exploring the Benefits of Training Expert Language Models over Instruction Tuningcited by 80
  23. 2024RLHF from Heterogeneous Feedback via Personalization and Preference Aggregationcited by 74
  24. 2024LoraRetriever: Input-Aware LoRA Retrieval and Composition for Mixed Tasks in the Wildcited by 68
  25. 2024Learning to Route Among Specialized Experts for Zero-Shot Generalizationcited by 65
  26. 2024HYDRA: Model Factorization Framework for Black-Box LLM Personalizationcited by 60
  27. 2024Persona-DB: Efficient Large Language Model Personalization for Response Prediction with Collaborative Data Refinementcited by 49
  28. 2023Teach LLMs to Personalize -- An Approach inspired by Writing Educationcited by 48
  29. 2020Evaluating Conversational Recommender Systems via User Simulationcited by 47
  30. 2023Everyone Deserves A Reward: Learning Customized Human Preferencescited by 43
  31. 2023Knowledge-Augmented Large Language Models for Personalized Contextual Query Suggestioncited by 43
  32. 2021One Chatbot Per Person: Creating Personalized Chatbots based on Implicit User Profilescited by 39
  33. 2023Expedited Training of Visual Conditioned Language Generation via Redundancy Reductioncited by 15

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 5; 2025: 38; 2026: 31.

74 papers.

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  1. 2025A Survey of Personalized Large Language Models: Progress and Future Directionscited by 71
  2. 2025UniCTokens: Boosting Personalized Understanding and Generation via Unified Concept Tokenscited by 56
  3. 2025A Survey on Personalized Alignment -- The Missing Piece for Large Language Models in Real-World Applicationscited by 42
  4. 2025Towards Holistic Evaluation of Large Audio-Language Models: A Comprehensive Surveycited by 39
  5. 2024Low-Rank Adaptation for Foundation Models: A Comprehensive Reviewcited by 37
  6. 2025Personalized Text Generation with Contrastive Activation Steeringcited by 34
  7. 2024LLMs + Persona-Plug = Personalized LLMscited by 32
  8. 2024AI PERSONA: Towards Life-long Personalization of LLMscited by 32
  9. 2025LaMP-QA: A Benchmark for Personalized Long-form Question Answeringcited by 31
  10. 2025From 1,000,000 Users to Every User: Scaling Up Personalized Preference for User-level Alignmentcited by 30
  11. 2025Think-While-Generating: On-the-Fly Reasoning for Personalized Long-Form Generationcited by 30
  12. 2025Reasoning-Enhanced Self-Training for Long-Form Personalized Text Generationcited by 27
38 more
  1. 2025A Survey on Personalized and Pluralistic Preference Alignment in Large Language Modelscited by 27
  2. 2025A Survey of Personalization: From RAG to Agentcited by 27
  3. 2025ExPerT: Effective and Explainable Evaluation of Personalized Long-Form Text Generationcited by 26
  4. 2025Modality-Aware Neuron Pruning for Unlearning in Multimodal Large Language Modelscited by 26
  5. 2025Retrieval Augmented Generation with Collaborative Filtering for Personalized Text Generationcited by 24
  6. 2025Teaching Language Models to Evolve with Users: Dynamic Profile Modeling for Personalized Alignmentcited by 24
  7. 2025How Far are LLMs from Being Our Digital Twins? A Benchmark for Persona-Based Behavior Chain Simulationcited by 22
  8. 2024Comparing Retrieval-Augmentation and Parameter-Efficient Fine-Tuning for Privacy-Preserving Personalization of Large Language Modelscited by 21
  9. 2025Instant Personalized Large Language Model Adaptation via Hypernetworkcited by 18
  10. 2024Personalized Image Generation with Large Multimodal Modelscited by 15
  11. 2025PersonaAgent: Bridging Memory and Action for Personalized LLM Agentscited by 14
  12. 2025CoSteer: Collaborative Decoding-Time Personalization via Local Delta Steeringcited by 13
  13. 2025The Era of Real-World Human Interaction: RL from User Conversationscited by 13
  14. 2025Beyond Profile: From Surface-Level Facts to Deep Persona Simulation in LLMscited by 9
  15. 2025A Desideratum for Conversational Agents: Capabilities, Challenges, and Future Directionscited by 9
  16. 2025Personalized Language Models via Privacy-Preserving Evolutionary Model Mergingcited by 8
  17. 2025SteerX: Disentangled Steering for LLM Personalizationcited by 7
  18. 2025Learning from Natural Language Feedback for Personalized Question Answeringcited by 5
  19. 2026Optimizing User Profiles via Contextual Bandits for Retrieval-Augmented LLM Personalizationcited by 5
  20. 2026CURP: Codebook-based Continuous User Representation for Personalized Generation with LLMscited by 4
  21. 2026Synthetic Interaction Data for Scalable Personalization in Large Language Modelscited by 4
  22. 2025Improving RAG for Personalization with Author Features and Contrastive Examplescited by 3
  23. 2025Modeling and Optimizing User Preferences in AI Copilots: A Comprehensive Survey and Taxonomycited by 3
  24. 2025Tagging the Thought: Unlocking Personalization Reasoning via Reinforcement Learningcited by 3
  25. 2026Text as a Universal Interface for Transferable Personalizationcited by 3
  26. 2026Bi-Mem: Bidirectional Construction of Hierarchical Memory for Personalized LLMs via Inductive-Reflective Agentscited by 3
  27. 2026Personal Visual Context Learning in Large Multimodal Modelscited by 3
  28. 2026Beyond Retrieval: Learning Compact User Representations for Scalable LLM Personalizationcited by 3
  29. 2025From Anger to Joy: How Nationality Personas Shape Emotion Attribution in Large Language Modelscited by 2
  30. 2025From Personal to Collective: On the Role of Local and Global Memory in LLM Personalizationcited by 2
  31. 2025Fints: Efficient Inference-Time Personalization for LLMs with Fine-Grained Instance-Tailored Steeringcited by 2
  32. 2025LLM-Generated Ads: From Personalization Parity to Persuasion Superioritycited by 2
  33. 2026Exploiting contextual information to improve stance detection in informal political discourse with LLMscited by 2
  34. 2025IROTE: Human-like Traits Elicitation of Large Language Model via In-Context Self-Reflective Optimizationcited by 1
  35. 2026PRISP: Privacy-Safe Few-Shot Personalization via Lightweight Adaptationcited by 1
  36. 2026Improving User Privacy in Personalized Generation: Client-Side Retrieval-Augmented Modification of Server-Side Generated Speculationscited by 1
  37. 2026Uncertainty-Aware Variational Reward Factorization via Probabilistic Preference Bases for LLM Personalizationcited by 1
  38. 2026TSUBASA: Improving Long-Horizon Personalization via Evolving Memory and Self-Learning with Context Distillationcited by 1

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