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Two Tales of Persona in LLMs:
A Survey of Role-Playing and Personalization

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Overview

Introduction

This is the official repository of the paper "Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalization", EMNLP 2024 Findings.

The concept of persona, originally adopted in dialogue literature, has re-surged as a promising framework for tailoring large language models (LLMs) to specific context (e.g., personalized search, LLM-as-a-judge). However, the growing research on leveraging persona in LLMs is relatively disorganized and lacks a systematic taxonomy. To close the gap, we present a comprehensive survey to categorize the current state of the field. We identify two lines of research, namely (1) LLM Role-Playing, where personas are assigned to LLMs, and (2) LLM Personalization, where LLMs take care of user personas. Additionally, we introduce existing methods for LLM personality evaluation. To the best of our knowledge, we present the first survey for role-playing and personalization in LLMs under the unified view of persona.

We continuously maintain this paper collection to foster future endeavors.

News

  • [2024.10.05] 🎯 We update the camera-ready version on arXiv. Click the link to check it out!
  • [2024.09.20] 🎊 Excited to share that our paper is accepted at EMNLP 2024 Findings! Hooray 🙌!
  • [2024.06.27] 🔥 We update an 8-page version on arXiv.
  • [2024.06.04] 🚀 Our paper is now available on arXiv and the reading list on GitHub.

Table of Contents

🙆‍♀️ LLM Role-Play (Adapt to Environment)

LLMs are tasked to play the assigned personas (i.e., roles) and act accordance to environmental feedback.

The key aspect is how LLMs adapt to defined environments.


LLM role-playing

💼 Workshops

Date Workshop Website Link
2405 LLMAgent @ ICLR ICLR 2024 Workshop on Large Language Model (LLM) Agents
2405 Agent Workshop @ CMU CMU Agent Workshop 2024

🌎 Environments

💻 Software Development

Date Authors Venue Paper
2308 Hong et al. ICLR MetaGPT: Meta Programming for Multi-Agent Collaborative Framework
2307 Qian et al. arXiv Communicative agents for software development
2305 Dong et al. TOSEM Self-collaboration code generation via chatgpt
2107 Chen et al. arXiv Evaluating large language models trained on code

🌐 Web

Date Authors Venue Paper
2404 Liu et al. arXiv VisualWebBench: How Far Have Multimodal LLMs Evolved in Web Page Understanding and Grounding?
2401 Zheng et al. LLMAgent @ ICLR GPT-4V(ision) is a Generalist Web Agent, if Grounded
2401 Koh et al. LLMAgent @ ICLR VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks
2401 Cheng et al. LLMAgent @ ICLR SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents
2312 Gur et al. EMNLP Understanding HTML with Large Language Models
2312 Hong et al. arXiv CogAgent: A Visual Language Model for GUI Agents
2307 Gur et al. ICLR A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis
2307 Zhou et al. ICLR WebArena: A Realistic Web Environment for Building Autonomous Agents
2306 Deng et al. NeurIPS Mind2web: Towards a generalist agent for the web
2303 Kim et al. NeurIPS Language Models can Solve Computer Tasks

🎮 Game

Date Authors Venue Paper
2310 Wang et al. EMNLP Humanoid Agents: Platform for Simulating Human-like Generative Agents
2305 Wang et al. TMLR Voyager: An open-ended embodied agent with large language models
2305 Fu et al. arXiv Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback
2304 Park et al. UIST Generative agents: Interactive simulacra of human behavior

🏥 Medical Application

Date Authors Venue Paper
2312 Kwon et al. AAAI Large Language Models are Clinical Reasoners: Reasoning-Aware Diagnosis Framework with Prompt-Generated Rationales
2311 Tang et al. arXiv Medagents: Large language models as collaborators for zero-shot medical reasoning
2307 Wu et al. ICLR Large Language Models Perform Diagnostic Reasoning
2207 Liévin et al. arXiv Can large language models reason about medical questions?

🧑‍⚖️ LLM as Evaluators

Date Authors Venue Paper
2308 Chan et al. ICLR ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate
2303 Wu et al. NLPCC Large Language Models are Diverse Role-Players for Summarization Evaluation

📦 General Framework

Date Authors Venue Paper
2405 Ahn, et al ACL Findings TimeChara: Evaluating Point-in-Time Character Hallucination of Role-Playing Large Language Models
2308 Chen et al. ICLR AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors
2307 Wang et al. NAACL Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration
2303 Li et al. NeurIPS CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society

🤖 Interaction & Behaviors

📊 Schemas

👤 Single-Agent
Date Authors Venue Paper
2401 Cheng et al. LLMAgent @ ICLR SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents
2401 Zheng et al. LLMAgent @ ICLR GPT-4V(ision) is a Generalist Web Agent, if Grounded
2312 Hong et al. arXiv CogAgent: A Visual Language Model for GUI Agents
2305 Wang et al. TMLR Voyager: An open-ended embodied agent with large language models
👥 Multi-Agent
Date Authors Venue Paper
2311 Tang et al. arXiv Medagents: Large language models as collaborators for zero-shot medical reasoning
2308 Chen et al. ICLR AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors
2308 Hong et al. ICLR MetaGPT: Meta Programming for Multi-Agent Collaborative Framework
2308 Chan et al. ICLR ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate
2307 Qian et al. arXiv Communicative agents for software development
2305 Fu et al. arXiv Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback

💡 Emergent Behaviors

Date Authors Venue Paper
2311 Tang et al. arXiv Medagents: Large language models as collaborators for zero-shot medical reasoning
2308 Chen et al. ICLR AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors
2307 Wang et al. NAACL Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration
2305 Fu et al. arXiv Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback
2303 Li et al. NeurIPS CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society

🙆‍♂️ LLM Personalization (Adapt to User)

LLMs are tasked to take care of users’ personas (e.g., background information, or historical behaviors) to meet customized needs.

The key aspect is how LLMs adapt to distinct users.

LLM personalization

💼 Workshops & Competitions

Date Authors Venue Paper
2403 Deshpande et al. PERSONALIZE @ EACL Proceedings of the 1st Workshop on Personalization of Generative AI Systems (PERSONALIZE 2024)
2310 Chen et al. Personalized Generative AI @ CIKM The First Workshop on Personalized Generative AI @ CIKM 2023: Personalization Meets Large Language Models
1902 Dinan et al. ConvAI2 @ NeurIPS The Second Conversational Intelligence Challenge (ConvAI2)
1808 Yusupov et al. ConvAI @ NeurIPS NIPS Conversational Intelligence Challenge 2017 Winner System: Skill-based Conversational Agent with Supervised Dialog Manager

📌 Tasks

💬 Personalized Dialogue

🔧 ToD Modeling

LLMs Era

Date Authors Venue Paper
2305 Yang et al. EMNLP RefGPT: Dialogue Generation of GPT, by GPT, and for GPT
2302 Li et al. NeurIPS Guiding large language models via directional stimulus prompting
2005 Hosseini-Asl et al. NeurIPS A Simple Language Model for Task-Oriented Dialogue
Comprehensive Paper List
Date Authors Venue Paper
2312 Xu et al. EMNLP Baize: An Open-Source Chat Model with Parameter-Efficient Tuning on Self-Chat Data
2309 Hu et al. arXiv Enhancing Large Language Model Induced Task-Oriented Dialogue Systems Through Look-Forward Motivated Goals
2308 Wu et al. SIGDIAL DiactTOD: Learning Generalizable Latent Dialogue Acts for Controllable Task-Oriented Dialogue Systems
2305 Yang et al. EMNLP RefGPT: Dialogue Generation of GPT, by GPT, and for GPT
2305 Bang et al. ACL Task-Optimized Adapters for an End-to-End Task-Oriented Dialogue System
2304 Ashby et al. CHI Personalized Quest and Dialogue Generation in Role-Playing Games: A Knowledge Graph and Language Model-based Approach
2304 Hudevcek et al. SIGDIAL Are Large Language Models All You Need for Task-Oriented Dialogue?
2302 Li et al. NeurIPS Guiding large language models via directional stimulus prompting
2302 Feng et al. ICLR Fantastic rewards and how to tame them: A case study on reward learning for task-oriented dialogue systems
2210 Huryn et al. COLING Automatic Generation of Large-scale Multi-turn Dialogues from Reddit
2108 Peng et al. TACL Soloist: Building Task Bots at Scale with Transfer Learning and Machine Teaching
2012 Yang et al. AAAI UBAR: Towards Fully End-to-End Task-Oriented Dialog Systems with GPT-2
2008 Madotto et al. arXiv Language models as few-shot learner for task-oriented dialogue systems
2005 Hosseini-Asl et al. NeurIPS A Simple Language Model for Task-Oriented Dialogue

Pre-LLMs Era

Date Authors Venue Paper
2006 Jianhong Wang et al. ICLR Modelling hierarchical structure between dialogue policy and natural language generator with option framework for task-oriented dialogue system
1606 N. Mrksic et al. ACL Neural Belief Tracker: Data-Driven Dialogue State Tracking
1506 Alessandro Sordoni et al. NAACL A Neural Network Approach to Context-Sensitive Generation of Conversational Responses
Comprehensive Paper List
Date Authors Venue Paper
2105 Sun et al. SIGIR Simulating user satisfaction for the evaluation of task-oriented dialogue systems
2006 Wang et al. ICLR Modelling hierarchical structure between dialogue policy and natural language generator with option framework for task-oriented dialogue system
2003 Yang et al. IEEE Multitask Learning and Reinforcement Learning for Personalized Dialog Generation: An Empirical Study
1912 Huang AAAI MALA: Cross-Domain Dialogue Generation with Action Learning
1910 Zhang et al. *SEM Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking
1905 Wu et al. ACL Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems
1807 Lei et al. ACL Sequicity: Simplifying Task-oriented Dialogue Systems with Single Sequence-to-Sequence Architectures
1804 Liu et al. NAACL Dialogue Learning with Human Teaching and Feedback in End-to-End Trainable Task-Oriented Dialogue Systems
1712 Rastogi et al. IEEE Scalable Multi-Domain Dialogue State Tracking
1709 Wu et al. AAAI StarSpace: Embed all the things!
1606 Miller et al. EMNLP Key-Value Memory Networks for Directly Reading Documents
1606 Mrksic et al. ACL Neural Belief Tracker: Data-Driven Dialogue State Tracking
1506 Sordoni et al. NAACL A Neural Network Approach to Context-Sensitive Generation of Conversational Responses
📝 User Persona Modeling
Date Authors Venue Paper
2405 Han ACL PSYDIAL: Personality-based Synthetic Dialogue Generation Using Large Language Models
2307 Tang et al. ACL Enhancing Personalized Dialogue Generation with Contrastive Latent Variables: Combining Sparse and Dense Persona
1807 Zhang et al. ACL Personalizing Dialogue Agents: I have a dog, do you have pets too?
Comprehensive Paper List
Date Authors Venue Paper
2405 Han ACL PSYDIAL: Personality-based Synthetic Dialogue Generation Using Large Language Models
2401 Lotfi et al. IEEE PersonalityChat: Conversation Distillation for Personalized Dialog Modeling with Facts and Traits
2401 Kim et al. EACL Commonsense-augmented Memory Construction and Management in Long-term Conversations via Context-aware Persona Refinement
2308 Tu et al. arXiv CharacterChat: Learning towards Conversational AI with Personalized Social Support
2307 Tang et al. ACL Enhancing Personalized Dialogue Generation with Contrastive Latent Variables: Combining Sparse and Dense Persona
2307 Ahn, et al ACL MPCHAT: Towards Multimodal Persona-Grounded Conversation
2011 Zhong et al. EMNLP Towards Persona-Based Empathetic Conversational Models
2007 Wu et al. ACL Guiding Variational Response Generator to Exploit Persona
2007 Liu et al. ACL You Impress Me: Dialogue Generation via Mutual Persona Perception
1911 Zheng et al. AAAI A Pre-Training Based Personalized Dialogue Generation Model with Persona-Sparse Data
1911 Song et al. AAAI Generating Persona Consistent Dialogues by Exploiting Natural Language Inference
1807 Zhang et al. ACL Personalizing Dialogue Agents: I have a dog, do you have pets too?

🛒 Recommendation System

Date Authors Venue Paper
2305 Yang et al. arXiv PALR: Personalization Aware LLMs for Recommendation
2304 Wang et al. arXiv Zero-Shot Next-Item Recommendation using Large Pretrained Language Models
2108 Li et al. ACL Personalized Transformer for Explainable Recommendation
Comprehensive Paper List
Date Authors Venue Paper
2405 Hu et al. WWW Enhancing sequential recommendation via llm-based semantic embedding learning
2311 Chen et al. arXiv A Survey on Large Language Models for Personalized and Explainable Recommendations
2308 Wang et al. arXiv RecMind: Large Language Model Powered Agent For Recommendation
2308 Chu et al. arXiv Leveraging Large Language Models for Pre-trained Recommender Systems
2306 Li et al. arXiv Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations
2305 Yang et al. arXiv PALR: Personalization Aware LLMs for Recommendation
2305 Zhang et al. arXiv Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach
2304 Wang et al. arXiv Zero-Shot Next-Item Recommendation using Large Pretrained Language Models
2208 Chen et al. KDD Personalized Chit-Chat Generation for Recommendation Using External Chat Corpora
2202 Li et al. TOIS Personalized Prompt Learning for Explainable Recommendation
2108 Li et al. ACL Personalized Transformer for Explainable Recommendation
Date Authors Venue Paper
2405 Zhou et al. WWW Cognitive personalized search integrating large language models with an efficient memory mechanism
2405 Baek et al. WWW Knowledge-Augmented Large Language Models for Personalized Contextual Query Suggestion
2405 Salemi arXiv Unified ranking for multiple retrieval-augmented large language models
2402 Sharma et al. CHI Generative echo chamber? effects of llm-powered search systems on diverse information seeking
2307 Eleni et al. arXiv Comparing Traditional and LLM-based Search for Consumer Choice: A Randomized Experiment
2307 Ziems et al. ACL Large Language Models are Built-in Autoregressive Search Engines
2107 Zhou et al. SIGIR Group based Personalized Search by Integrating Search Behaviour and Friend Network

🩺 Personalized Healthcare

Date Authors Venue Paper
2402 Abbasian et al. arXiv Knowledge-Infused LLM-Powered Conversational Health Agent: A Case Study for Diabetes Patients
2402 Jin et al. arXiv Health-LLM: Personalized Retrieval-Augmented Disease Prediction System
2310 Abbasian et al. arXiv Conversational Health Agents: A Personalized LLM-Powered Agent Framework
2309 Zhang et al. arXiv LLM-based Medical Assistant Personalization with Short- and Long-Term Memory Coordination

📚 Personalized Education

Date Authors Venue Paper
2403 Park et al. CHI Empowering personalized learning through a conversation-based tutoring system with student modeling
2308 Dan et al. arXiv Educhat: A large-scale language model-based chatbot system for intelligent education
2307 Shehata et al. BEA @ ACL Enhancing Video-based Learning Using Knowledge Tracing: Personalizing Students’ Learning Experience with ORBITS

🛠️ Methods

🎛️ Fine-Tuning

Date Authors Venue Paper
2403 Mondal et al. EACL Presentations by the Humans and For the Humans: Harnessing LLMs for Generating Persona-Aware Slides from Documents
2402 Li et al. arXiv Personalized Language Modeling from Personalized Human Feedback
2402 Tan et al. arXiv Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning
2312 Hwang et al. arXiv Promptable Behaviors: Personalizing Multi-Objective Rewards from Human Preferences
2312 Shea et al. EMNLP Building Persona Consistent Dialogue Agents with Offline Reinforcement Learning
2311 Qin et al. arXiv Enabling on-device large language model personalization with self-supervised data selection and synthesis
2310 Jang et al. arXiv Personalized large language model alignment via post-hoc parameter merging
2303 Kirk et al. arXiv Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedback

🔗 Retrieval Augmentation

Date Authors Venue Paper
2404 Zhang et al. arXiv Personalized LLM Response Generation with Parameterized Memory Injection
2403 Zhong et al. AAAI MemoryBank: Enhancing Large Language Models with Long-Term Memory
2402 Sun et al. arXiv Persona-DB: Efficient Large Language Model Personalization for Response Prediction with Collaborative Data Refinement
2402 Tan et al. arXiv Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning
2205 Fu et al. ACL There Are a Thousand Hamlets in a Thousand People’s Eyes: Enhancing Knowledge-grounded Dialogue with Personal Memory
2106 Wu et al. NAACL Personalized Response Generation via Generative Split Memory Network

✍️ Prompting

📄 Vanilla Personalized Prompt
Date Authors Venue Paper
2305 Dai et al. RecSys Uncovering ChatGPT’s Capabilities in Recommender Systems
2305 Christakopoulou et al. arXiv Large Language Models for User Interest Journeys
2305 Zhiyuli et al. arXiv BookGPT: A General Framework for Book Recommendation Empowered by Large Language Model
🔦 Retrieval-Augmented Personalized Prompt
Date Authors Venue Paper
2311 Mysore et al. arXiv PEARL: Personalizing Large Language Model Writing Assistants with Generation-Calibrated Retrievers
2308 Li et al. arXiv Teach LLMs to Personalize -- An Approach inspired by Writing Education
2304 Salemi et al. arXiv LaMP: When Large Language Models Meet Personalization
📂 Profile-Augmented Prompt
Date Authors Venue Paper
2405 Li et al. WWW Learning to Rewrite Prompts for Personalized Text Generation
2310 Richardson et al. arXiv Integrating Summarization and Retrieval for Enhanced Personalization via Large Language Models
2305 Liu et al. WSDM ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models

🧐 LLM Personality Evaluation

Date Authors Venue Paper
2401 Huang et al. ICLR On the Humanity of Conversational AI: Evaluating the Psychological Portrayal of LLMs
2309 Jiang et al. NeurIPS Evaluating and inducing personality in pre-trained language models
2307 Fang et al. ACL On Text-based Personality Computing: Challenges and Future Directions
Comprehensive Paper List
Date Authors Venue Paper
2403 Sorokovikova et al. PERSONALIZE @ EACL LLMs Simulate Big5 Personality Traits: Further Evidence
2403 Frisch et al. PERSONALIZE @ EACL LLM Agents in Interaction: Measuring Personality Consistency and Linguistic Alignment in Interacting Populations of Large Language Models
2402 Song et al. arXiv Identifying Multiple Personalities in Large Language Models with External Evaluation
2402 Song et al. arXiv Identifying Multiple Personalities in Large Language Models with External Evaluation
2402 Yang et al. arXiv LLM Agents for Psychology: A Study on Gamified Assessments
2401 Huang et al. ICLR On the Humanity of Conversational AI: Evaluating the Psychological Portrayal of LLMs
2312 Rao et al. EMNLP Can ChatGPT Assess Human Personalities? A General Evaluation Framework
2311 Dorner et al. SoLaR @ NeurIPS Do personality tests generalize to large language models?
2310 Wang et al. arXiv InCharacter: Evaluating Personality Fidelity in Role-Playing Agents through Psychological Interviews
2309 Jiang et al. NeurIPS Evaluating and inducing personality in pre-trained language models
2307 Pan et al. arXiv Do LLMs Possess a Personality? Making the MBTI Test an Amazing Evaluation for Large Language Models
2307 Fang et al. ACL On Text-based Personality Computing: Challenges and Future Directions
2307 Ji et al. arXiv Is ChatGPT a Good Personality Recognizer? A Preliminary Study
2305 Jiang et al. arXiv Personallm: Investigating the ability of large language models to express big five personality traits

🌱 How to contribute

✨ Welcome to contribute to this reading list via 📝 Issues using the following format.

Date Authors Venue Paper
1706 Vaswani, et al NeurIPS Attention Is All You Need

🔖 Citation

📚 If you find our survey beneficial for your research, please kindly cite our paper :-)

@misc{tseng2024talespersonallmssurvey,
  title={Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalization},
  author={Yu-Min Tseng and Yu-Chao Huang and Teng-Yun Hsiao and Wei-Lin Chen and Chao-Wei Huang and Yu Meng and Yun-Nung Chen},
  year={2024},
  eprint={2406.01171},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2406.01171},
}

🖌️ Authors

Yu-Min Tseng*, Yu-Chao Huang*, Teng-Yun Hsiao*, Wei-Lin Chen*, Chao-Wei Huang, Yu Meng, Yun-Nung Chen.

(* Equal Contribution.) (Acknowlegement: Yu-Ching Hsu, Jia-Yin Foo.)

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