## News
- [2024.06.27] :fire: We update an 8-page version on [arXiv](https://arxiv.org/abs/2406.01171).
- [2024.06.04] :rocket: Our paper is now available on [arXiv](https://arxiv.org/abs/2406.01171) and the reading list on [GitHub](https://github.com/MiuLab/PersonaLLM-Survey).
## Table of Contents
- [๐โโ๏ธ LLM Role-Play (Adapt to Environment)](#llm-role-play-adapt-to-environment)
- [๐ผ Workshops](#role-playing-workshops)
- [๐ Environments](#environments)
- [๐ป Software Development](#software-development)
- [๐ Web](#web)
- [๐ฎ Game](#game)
- [๐ฅ Medical Application](#medical-application)
- [๐งโโ๏ธ LLM as Evaluators](#llm-as-evaluators)
- [๐ฆ General Framework](#general-framework)
- [๐ค Agentic Interactions](#agentic-interactions)
- [๐ Schemas](#schemas)
- [๐ค Single-Agent](#single-agent)
- [๐ฅ Multi-Agent](#multi-agent)
- [๐ก Emergent Behaviors](#emergent-behaviors)
- [๐โโ๏ธ LLM Personalization (Adapt to User)](#llm-personalization-adapt-to-user)
- [๐ผ Workshops & Competitions](#personalization-workshops)
- [๐ Tasks](#tasks)
- [๐ฌ Personalized Dialogue](#personalized-dialogue)
- [๐ง ToD Modeling](#tod-modeling)
- [๐ User Persona Modeling](#user-persona-modeling)
- [๐ Recommendation System](#recommendation-system)
- [๐ Personalized Search](#personalized-search)
- [๐ฉบ Personalized Healthcare](#personalized-healthcare)
- [๐ Personalized Education](#personalized-education)
- [๐ ๏ธ Methods](#methods)
- [๐๏ธ Fine-Tuning](#fine-tuning)
- [๐ Retrieval Augmentation](#retrieval-augmentation)
- [โ๏ธ Prompting](#prompting)
- [๐ Vanilla Personalized Prompt](#vanilla-personalized-prompt)
- [๐ฆ Retrieval-Augmented Personalized Prompt](#retrieval-augmented-personalized-prompt)
- [๐ Profile-Augmented Prompt](#profile-augmented-prompt)
- [๐ง LLM Personality Evaluation](#llm-personality-evaluation)
- [๐ฑ How to contribute](#how-to-contribute)
- [๐ Citation](#citation)
- [๐๏ธ Authors](#authors)
๐โโ๏ธ 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*.
๐ผ Workshops
| Date | Workshop | Website Link |
|:-----:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2405 | LLMAgent @ ICLR | [ICLR 2024 Workshop on Large Language Model (LLM) Agents](https://llmagents.github.io/) |
| 2405 | Agent Workshop @ CMU | [CMU Agent Workshop 2024](https://cmu-agent-workshop.github.io/) |
๐ Environments
๐ป Software Development
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2308 | Hong et al. | ICLR | [MetaGPT: Meta Programming for Multi-Agent Collaborative Framework](https://arxiv.org/abs/2308.00352) |
| 2307 | Qian et al. | arXiv | [Communicative agents for software development](https://arxiv.org/abs/2307.07924) |
| 2305 | Dong et al. | TOSEM | [Self-collaboration code generation via chatgpt](https://arxiv.org/abs/2304.07590) |
| 2107 | Chen et al. | arXiv | [Evaluating large language models trained on code](https://arxiv.org/abs/2107.03374) |
๐ Web
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2404 | Liu et al. | arXiv | [VisualWebBench: How Far Have Multimodal LLMs Evolved in Web Page Understanding and Grounding?](https://arxiv.org/abs/2404.05955v1) |
| 2401 | Zheng et al. | LLMAgent @ ICLR | [GPT-4V(ision) is a Generalist Web Agent, if Grounded](https://arxiv.org/abs/2401.01614) |
| 2401 | Koh et al. | LLMAgent @ ICLR | [VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks](https://arxiv.org/abs/2401.13649) |
| 2401 | Cheng et al. | LLMAgent @ ICLR | [SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents](https://arxiv.org/abs/2401.10935) |
| 2312 | Gur et al. | EMNLP | [Understanding HTML with Large Language Models](https://aclanthology.org/2023.findings-emnlp.185/) |
| 2312 | Hong et al. | arXiv | [CogAgent: A Visual Language Model for GUI Agents](https://arxiv.org/abs/2312.08914) |
| 2307 | Gur et al. | ICLR | [A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis](https://arxiv.org/abs/2307.12856) |
| 2307 | Zhou et al. | ICLR | [WebArena: A Realistic Web Environment for Building Autonomous Agents](https://arxiv.org/abs/2307.13854) |
| 2306 | Deng et al. | NeurIPS | [Mind2web: Towards a generalist agent for the web](https://arxiv.org/abs/2306.06070) |
| 2303 | Kim et al. | NeurIPS | [Language Models can Solve Computer Tasks](https://arxiv.org/abs/2303.17491) |
๐ฎ Game
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2310 | Wang et al. | EMNLP | [Humanoid Agents: Platform for Simulating Human-like Generative Agents](https://arxiv.org/abs/2310.05418) |
| 2305 | Wang et al. | TMLR | [Voyager: An open-ended embodied agent with large language models](https://arxiv.org/abs/2305.16291) |
| 2305 | Fu et al. | arXiv | [Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback](https://arxiv.org/abs/2305.10142) |
| 2304 | Park et al. | UIST | [Generative agents: Interactive simulacra of human behavior](https://arxiv.org/abs/2304.03442) |
๐ฅ 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](https://arxiv.org/abs/2312.07399) |
| 2311 | Tang et al. | arXiv | [Medagents: Large language models as collaborators for zero-shot medical reasoning](https://arxiv.org/abs/2311.10537) |
| 2307 | Wu et al. | ICLR | [Large Language Models Perform Diagnostic Reasoning](https://arxiv.org/abs/2307.08922) |
| 2207 | Liรฉvin et al. | arXiv | [Can large language models reason about medical questions?](https://arxiv.org/abs/2207.08143) |
๐งโโ๏ธ LLM as Evaluators
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2308 | Chan et al. | ICLR | [ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate](https://arxiv.org/abs/2308.07201) |
| 2303 | Wu et al. | NLPCC | [Large Language Models are Diverse Role-Players for Summarization Evaluation](https://arxiv.org/abs/2303.15078) |
๐ฆ 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](https://arxiv.org/abs/2405.18027) |
| 2308 | Chen et al. | ICLR | [AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors](https://arxiv.org/abs/2308.10848) |
| 2307 | Wang et al. | NAACL | [Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration](https://arxiv.org/abs/2307.05300) |
| 2303 | Li et al. | NeurIPS | [CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society](https://arxiv.org/abs/2303.17760) |
๐ค Interaction & Behaviors
๐ Schemas
๐ค Single-Agent
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2401 | Cheng et al. | LLMAgent @ ICLR | [SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents](https://arxiv.org/abs/2401.10935) |
| 2401 | Zheng et al. | LLMAgent @ ICLR | [GPT-4V(ision) is a Generalist Web Agent, if Grounded](https://arxiv.org/abs/2401.01614) |
| 2312 | Hong et al. | arXiv | [CogAgent: A Visual Language Model for GUI Agents](https://arxiv.org/abs/2312.08914) |
| 2305 | Wang et al. | TMLR | [Voyager: An open-ended embodied agent with large language models](https://arxiv.org/abs/2305.16291) |
๐ฅ Multi-Agent
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2311 | Tang et al. | arXiv | [Medagents: Large language models as collaborators for zero-shot medical reasoning](https://arxiv.org/abs/2311.10537) |
| 2308 | Chen et al. | ICLR | [AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors](https://arxiv.org/abs/2308.10848) |
| 2308 | Hong et al. | ICLR | [MetaGPT: Meta Programming for Multi-Agent Collaborative Framework](https://arxiv.org/abs/2308.00352) |
| 2308 | Chan et al. | ICLR | [ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate](https://arxiv.org/abs/2308.07201) |
| 2307 | Qian et al. | arXiv | [Communicative agents for software development](https://arxiv.org/abs/2307.07924) |
| 2305 | Fu et al. | arXiv | [Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback](https://arxiv.org/abs/2305.10142) |
๐ก Emergent Behaviors
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2311 | Tang et al. | arXiv | [Medagents: Large language models as collaborators for zero-shot medical reasoning](https://arxiv.org/abs/2311.10537) |
| 2308 | Chen et al. | ICLR | [AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors](https://arxiv.org/abs/2308.10848) |
| 2307 | Wang et al. | NAACL | [Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration](https://arxiv.org/abs/2307.05300) |
| 2305 | Fu et al. | arXiv | [Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback](https://arxiv.org/abs/2305.10142) |
| 2303 | Li et al. | NeurIPS | [CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society](https://arxiv.org/abs/2303.17760) |
๐โโ๏ธ LLM Personalization (Adapt to User)
LLMs are tasked to take care of usersโ personas (e.g., background information, or historical behaviors) to meet customized needs.
The key aspect is *how LLMs adapt to distinct users*.
๐ผ 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)](https://aclanthology.org/volumes/2024.personalize-1/) |
| 2310 | Chen et al. | Personalized Generative AI @ CIKM | [The First Workshop on Personalized Generative AI @ CIKM 2023: Personalization Meets Large Language Models](https://dl.acm.org/doi/abs/10.1145/3583780.3615314) |
| 1902 | Dinan et al. | ConvAI2 @ NeurIPS | [The Second Conversational Intelligence Challenge (ConvAI2)](https://arxiv.org/abs/1902.00098) |
| 1808 | Yusupov et al. | ConvAI @ NeurIPS | [NIPS Conversational Intelligence Challenge 2017 Winner System: Skill-based Conversational Agent with Supervised Dialog Manager](https://aclanthology.org/C18-1312/) |
๐ Tasks
๐ฌ Personalized Dialogue
๐ง ToD Modeling
LLMs Era
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2305 | Yang et al. | EMNLP | [RefGPT: Dialogue Generation of GPT, by GPT, and for GPT](https://aclanthology.org/2023.findings-emnlp.165/) |
| 2302 | Li et al. | NeurIPS | [Guiding large language models via directional stimulus prompting](https://arxiv.org/abs/2302.11520) |
| 2005 | Hosseini-Asl et al. | NeurIPS | [A Simple Language Model for Task-Oriented Dialogue](https://arxiv.org/abs/2005.00796) |
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](https://aclanthology.org/2023.emnlp-main.385/) |
| 2309 | Hu et al. | arXiv | [Enhancing Large Language Model Induced Task-Oriented Dialogue Systems Through Look-Forward Motivated Goals](https://arxiv.org/abs/2309.08949) |
| 2308 | Wu et al. | SIGDIAL | [DiactTOD: Learning Generalizable Latent Dialogue Acts for Controllable Task-Oriented Dialogue Systems](https://aclanthology.org/2023.sigdial-1.24.pdf) |
| 2305 | Yang et al. | EMNLP | [RefGPT: Dialogue Generation of GPT, by GPT, and for GPT](https://aclanthology.org/2023.findings-emnlp.165/) |
| 2305 | Bang et al. | ACL | [Task-Optimized Adapters for an End-to-End Task-Oriented Dialogue System](https://aclanthology.org/2023.findings-acl.464/) |
| 2304 | Ashby et al. | CHI | [Personalized Quest and Dialogue Generation in Role-Playing Games: A Knowledge Graph and Language Model-based Approach](https://dl.acm.org/doi/10.1145/3544548.3581441) |
| 2304 | Hudevcek et al. | SIGDIAL | [Are Large Language Models All You Need for Task-Oriented Dialogue?](https://aclanthology.org/2023.sigdial-1.21/) |
| 2302 | Li et al. | NeurIPS | [Guiding large language models via directional stimulus prompting](https://arxiv.org/abs/2302.11520) |
| 2302 | Feng et al. | ICLR | [Fantastic rewards and how to tame them: A case study on reward learning for task-oriented dialogue systems](https://arxiv.org/abs/2302.10342) |
| 2210 | Huryn et al. | COLING | [Automatic Generation of Large-scale Multi-turn Dialogues from Reddit](https://aclanthology.org/2022.coling-1.297/) |
| 2108 | Peng et al. | TACL | [Soloist: Building Task Bots at Scale with Transfer Learning and Machine Teaching](https://aclanthology.org/2021.tacl-1.49/) |
| 2012 | Yang et al. | AAAI | [UBAR: Towards Fully End-to-End Task-Oriented Dialog Systems with GPT-2](https://arxiv.org/abs/2012.03539) |
| 2008 | Madotto et al. | arXiv | [Language models as few-shot learner for task-oriented dialogue systems](https://arxiv.org/abs/2008.06239) |
| 2005 | Hosseini-Asl et al. | NeurIPS | [A Simple Language Model for Task-Oriented Dialogue](https://arxiv.org/abs/2005.00796) |
---
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](https://arxiv.org/abs/2006.06814) |
| 1606 | N. Mrksic et al. | ACL | [Neural Belief Tracker: Data-Driven Dialogue State Tracking](https://aclanthology.org/P17-1163/) |
| 1506 | Alessandro Sordoni et al. | NAACL | [A Neural Network Approach to Context-Sensitive Generation of Conversational Responses](https://aclanthology.org/N15-1020/) |
Comprehensive Paper List
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2105 | Sun et al. | SIGIR | [Simulating user satisfaction for the evaluation of task-oriented dialogue systems](https://arxiv.org/abs/2105.03748) |
| 2006 | Wang et al. | ICLR | [Modelling hierarchical structure between dialogue policy and natural language generator with option framework for task-oriented dialogue system](https://arxiv.org/abs/2006.06814) |
| 2003 | Yang et al. | IEEE | [Multitask Learning and Reinforcement Learning for Personalized Dialog Generation: An Empirical Study](https://ieeexplore.ieee.org/abstract/document/9025776) |
| 1912 | Huang | AAAI | [MALA: Cross-Domain Dialogue Generation with Action Learning](https://arxiv.org/abs/1912.08442) |
| 1910 | Zhang et al. | *SEM | [Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking](https://aclanthology.org/2020.starsem-1.17/) |
| 1905 | Wu et al. | ACL | [Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems](https://aclanthology.org/P19-1078/) |
| 1807 | Lei et al. | ACL | [Sequicity: Simplifying Task-oriented Dialogue Systems with Single Sequence-to-Sequence Architectures](https://aclanthology.org/P18-1133/) |
| 1804 | Liu et al. | NAACL | [Dialogue Learning with Human Teaching and Feedback in End-to-End Trainable Task-Oriented Dialogue Systems](https://aclanthology.org/N18-1187/) |
| 1712 | Rastogi et al. | IEEE | [Scalable Multi-Domain Dialogue State Tracking](https://arxiv.org/abs/1712.10224) |
| 1709 | Wu et al. | AAAI | [StarSpace: Embed all the things!](https://arxiv.org/abs/1709.03856) |
| 1606 | Miller et al. | EMNLP | [Key-Value Memory Networks for Directly Reading Documents](https://aclanthology.org/D16-1147/) |
| 1606 | Mrksic et al. | ACL | [Neural Belief Tracker: Data-Driven Dialogue State Tracking](https://aclanthology.org/P17-1163/) |
| 1506 | Sordoni et al. | NAACL | [A Neural Network Approach to Context-Sensitive Generation of Conversational Responses](https://aclanthology.org/N15-1020/) |
๐ User Persona Modeling
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2405 | Han | ACL | [PSYDIAL: Personality-based Synthetic Dialogue Generation Using Large Language Models](https://aclanthology.org/2024.lrec-main.1166/) |
| 2307 | Tang et al. | ACL | [Enhancing Personalized Dialogue Generation with Contrastive Latent Variables: Combining Sparse and Dense Persona](https://aclanthology.org/2023.acl-long.299/) |
| 1807 | Zhang et al. | ACL | [Personalizing Dialogue Agents: I have a dog, do you have pets too?](https://aclanthology.org/P18-1205/) |
Comprehensive Paper List
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2405 | Han | ACL | [PSYDIAL: Personality-based Synthetic Dialogue Generation Using Large Language Models](https://aclanthology.org/2024.lrec-main.1166/) |
| 2401 | Lotfi et al. | IEEE | [PersonalityChat: Conversation Distillation for Personalized Dialog Modeling with Facts and Traits](https://arxiv.org/abs/2401.07363) |
| 2401 | Kim et al. | EACL | [Commonsense-augmented Memory Construction and Management in Long-term Conversations via Context-aware Persona Refinement](https://arxiv.org/abs/2401.14215) |
| 2308 | Tu et al. | arXiv | [CharacterChat: Learning towards Conversational AI with Personalized Social Support](https://arxiv.org/abs/2308.10278) |
| 2307 | Tang et al. | ACL | [Enhancing Personalized Dialogue Generation with Contrastive Latent Variables: Combining Sparse and Dense Persona](https://aclanthology.org/2023.acl-long.299/) |
| 2307 | Ahn, et al | ACL | [MPCHAT: Towards Multimodal Persona-Grounded Conversation](https://aclanthology.org/2023.acl-long.189/) |
| 2011 | Zhong et al. | EMNLP | [Towards Persona-Based Empathetic Conversational Models](https://aclanthology.org/2020.emnlp-main.531/) |
| 2007 | Wu et al. | ACL | [Guiding Variational Response Generator to Exploit Persona](https://aclanthology.org/2020.acl-main.7/) |
| 2007 | Liu et al. | ACL | [You Impress Me: Dialogue Generation via Mutual Persona Perception](https://aclanthology.org/2020.acl-main.131/) |
| 1911 | Zheng et al. | AAAI | [A Pre-Training Based Personalized Dialogue Generation Model with Persona-Sparse Data](https://arxiv.org/abs/1911.04700) |
| 1911 | Song et al. | AAAI | [Generating Persona Consistent Dialogues by Exploiting Natural Language Inference](https://arxiv.org/abs/1911.05889) |
| 1807 | Zhang et al. | ACL | [Personalizing Dialogue Agents: I have a dog, do you have pets too?](https://aclanthology.org/P18-1205/) |
๐ Recommendation System
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2305 | Yang et al. | arXiv | [PALR: Personalization Aware LLMs for Recommendation](https://arxiv.org/abs/2305.07622) |
| 2304 | Wang et al. | arXiv | [Zero-Shot Next-Item Recommendation using Large Pretrained Language Models](https://arxiv.org/abs/2304.03153) |
| 2108 | Li et al. | ACL | [Personalized Transformer for Explainable Recommendation](https://aclanthology.org/2021.acl-long.383/) |
Comprehensive Paper List
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2405 | Hu et al. | WWW | [Enhancing sequential recommendation via llm-based semantic embedding learning](https://dl.acm.org/doi/abs/10.1145/3589335.3648307) |
| 2311 | Chen et al. | arXiv | [A Survey on Large Language Models for Personalized and Explainable Recommendations](https://arxiv.org/abs/2311.12338) |
| 2308 | Wang et al. | arXiv | [RecMind: Large Language Model Powered Agent For Recommendation](https://arxiv.org/abs/2308.14296) |
| 2308 | Chu et al. | arXiv | [Leveraging Large Language Models for Pre-trained Recommender Systems](https://arxiv.org/abs/2308.10837) |
| 2306 | Li et al. | arXiv | [Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations](https://arxiv.org/abs/2306.01475) |
| 2305 | Yang et al. | arXiv | [PALR: Personalization Aware LLMs for Recommendation](https://arxiv.org/abs/2305.07622) |
| 2305 | Zhang et al. | arXiv | [Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach](https://arxiv.org/abs/2305.07001) |
| 2304 | Wang et al. | arXiv | [Zero-Shot Next-Item Recommendation using Large Pretrained Language Models](https://arxiv.org/abs/2304.03153) |
| 2208 | Chen et al. | KDD | [Personalized Chit-Chat Generation for Recommendation Using External Chat Corpora](https://dl.acm.org/doi/abs/10.1145/3534678.3539215) |
| 2202 | Li et al. | TOIS | [Personalized Prompt Learning for Explainable Recommendation](https://arxiv.org/abs/2202.07371) |
| 2108 | Li et al. | ACL | [Personalized Transformer for Explainable Recommendation](https://aclanthology.org/2021.acl-long.383/) |
๐ Personalized Search
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2405 | Zhou et al. | WWW | [Cognitive personalized search integrating large language models with an efficient memory mechanism](https://arxiv.org/abs/2402.10548) |
| 2405 | Baek et al. | WWW | [Knowledge-Augmented Large Language Models for Personalized Contextual Query Suggestion](https://arxiv.org/abs/2311.06318) |
| 2405 | Salemi | arXiv | [Unified ranking for multiple retrieval-augmented large language models](https://arxiv.org/abs/2405.00175) |
| 2402 | Sharma et al. | CHI | [Generative echo chamber? effects of llm-powered search systems on diverse information seeking](https://arxiv.org/abs/2402.05880) |
| 2307 | Eleni et al. | arXiv | [Comparing Traditional and LLM-based Search for Consumer Choice: A Randomized Experiment](https://arxiv.org/abs/2307.03744) |
| 2307 | Ziems et al. | ACL | [Large Language Models are Built-in Autoregressive Search Engines](https://arxiv.org/abs/2305.09612) |
| 2107 | Zhou et al. | SIGIR | [Group based Personalized Search by Integrating Search Behaviour and Friend Network](https://arxiv.org/abs/2111.12618) |
๐ฉบ Personalized Healthcare
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2402 | Abbasian et al. | arXiv | [Knowledge-Infused LLM-Powered Conversational Health Agent: A Case Study for Diabetes Patients](https://arxiv.org/abs/2402.10153) |
| 2402 | Jin et al. | arXiv | [Health-LLM: Personalized Retrieval-Augmented Disease Prediction System](https://arxiv.org/abs/2402.00746) |
| 2310 | Abbasian et al. | arXiv | [Conversational Health Agents: A Personalized LLM-Powered Agent Framework](https://arxiv.org/abs/2310.02374) |
| 2309 | Zhang et al. | arXiv | [LLM-based Medical Assistant Personalization with Short- and Long-Term Memory Coordination](https://arxiv.org/abs/2309.11696) |
๐ Personalized Education
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2403 | Park et al. | CHI | [Empowering personalized learning through a conversation-based tutoring system with student modeling](https://arxiv.org/abs/2403.14071) |
| 2308 | Dan et al. | arXiv | [Educhat: A large-scale language model-based chatbot system for intelligent education](https://arxiv.org/abs/2308.02773) |
| 2307 | Shehata et al. | BEA @ ACL | [Enhancing Video-based Learning Using Knowledge Tracing: Personalizing Studentsโ Learning Experience with ORBITS](https://aclanthology.org/2023.bea-1.8/) |
๐ ๏ธ Methods
๐๏ธ 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](https://aclanthology.org/2024.eacl-long.163/) |
| 2402 | Li et al. | arXiv | [Personalized Language Modeling from Personalized Human Feedback](https://arxiv.org/abs/2402.05133) |
| 2402 | Tan et al. | arXiv | [Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning](https://arxiv.org/abs/2402.04401) |
| 2312 | Hwang et al. | arXiv | [Promptable Behaviors: Personalizing Multi-Objective Rewards from Human Preferences](https://arxiv.org/abs/2312.09337) |
| 2312 | Shea et al. | EMNLP | [Building Persona Consistent Dialogue Agents with Offline Reinforcement Learning](https://arxiv.org/abs/2310.10735) |
| 2311 | Qin et al. | arXiv | [Enabling on-device large language model personalization with self-supervised data selection and synthesis](https://arxiv.org/abs/2311.12275) |
| 2310 | Jang et al. | arXiv | [Personalized large language model alignment via post-hoc parameter merging](https://arxiv.org/abs/2310.11564) |
| 2303 | Kirk et al. | arXiv | [Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedback](https://arxiv.org/abs/2303.05453) |
๐ Retrieval Augmentation
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2404 | Zhang et al. | arXiv | [Personalized LLM Response Generation with Parameterized Memory Injection](https://arxiv.org/abs/2404.03565) |
| 2403 | Zhong et al. | AAAI | [MemoryBank: Enhancing Large Language Models with Long-Term Memory](https://ojs.aaai.org/index.php/AAAI/article/view/29946) |
| 2402 | Sun et al. | arXiv | [Persona-DB: Efficient Large Language Model Personalization for Response Prediction with Collaborative Data Refinement](https://arxiv.org/abs/2402.11060) |
| 2402 | Tan et al. | arXiv | [Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning](https://arxiv.org/abs/2402.04401) |
| 2205 | Fu et al. | ACL | [There Are a Thousand Hamlets in a Thousand Peopleโs Eyes: Enhancing Knowledge-grounded Dialogue with Personal Memory](https://aclanthology.org/2022.acl-long.270/) |
| 2106 | Wu et al. | NAACL | [Personalized Response Generation via Generative Split Memory Network](https://aclanthology.org/2021.naacl-main.157/) |
โ๏ธ Prompting
๐ Vanilla Personalized Prompt
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2305 | Dai et al. | RecSys | [Uncovering ChatGPTโs Capabilities in Recommender Systems](https://arxiv.org/abs/2305.02182) |
| 2305 | Christakopoulou et al. | arXiv | [Large Language Models for User Interest Journeys](https://arxiv.org/abs/2305.15498) |
| 2305 | Zhiyuli et al. | arXiv | [BookGPT: A General Framework for Book Recommendation Empowered by Large Language Model](https://arxiv.org/abs/2305.15673) |
๐ฆ Retrieval-Augmented Personalized Prompt
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2311 | Mysore et al. | arXiv | [PEARL: Personalizing Large Language Model Writing Assistants with Generation-Calibrated Retrievers](https://arxiv.org/abs/2311.09180) |
| 2308 | Li et al. | arXiv | [Teach LLMs to Personalize -- An Approach inspired by Writing Education](https://arxiv.org/abs/2308.07968) |
| 2304 | Salemi et al. | arXiv | [LaMP: When Large Language Models Meet Personalization](https://arxiv.org/abs/2304.11406) |
๐ Profile-Augmented Prompt
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2405 | Li et al. | WWW | [Learning to Rewrite Prompts for Personalized Text Generation](https://dl.acm.org/doi/10.1145/3589334.3645408) |
| 2310 | Richardson et al. | arXiv | [Integrating Summarization and Retrieval for Enhanced Personalization via Large Language Models](https://arxiv.org/abs/2310.20081) |
| 2305 | Liu et al. | WSDM | [ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models](https://arxiv.org/abs/2305.06566) |
๐ง LLM Personality Evaluation
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2401 | Huang et al. | ICLR | [On the Humanity of Conversational AI: Evaluating the Psychological Portrayal of LLMs](https://openreview.net/forum?id=H3UayAQWoE) |
| 2309 | Jiang et al. | NeurIPS | [Evaluating and inducing personality in pre-trained language models](https://arxiv.org/abs/2206.07550) |
| 2307 | Fang et al. | ACL | [On Text-based Personality Computing: Challenges and Future Directions](https://aclanthology.org/2023.findings-acl.691/) |
Comprehensive Paper List
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 2403 | Sorokovikova et al. | PERSONALIZE @ EACL | [LLMs Simulate Big5 Personality Traits: Further Evidence](https://aclanthology.org/2024.personalize-1.7/) |
| 2403 | Frisch et al. | PERSONALIZE @ EACL | [LLM Agents in Interaction: Measuring Personality Consistency and Linguistic Alignment in Interacting Populations of Large Language Models](https://aclanthology.org/2024.personalize-1.9/) |
| 2402 | Song et al. | arXiv | [Identifying Multiple Personalities in Large Language Models with External Evaluation](https://arxiv.org/abs/2402.14805) |
| 2402 | Song et al. | arXiv | [Identifying Multiple Personalities in Large Language Models with External Evaluation](https://arxiv.org/abs/2402.14805) |
| 2402 | Yang et al. | arXiv | [LLM Agents for Psychology: A Study on Gamified Assessments](https://arxiv.org/abs/2402.12326) |
| 2401 | Huang et al. | ICLR | [On the Humanity of Conversational AI: Evaluating the Psychological Portrayal of LLMs](https://openreview.net/forum?id=H3UayAQWoE) |
| 2312 | Rao et al. | EMNLP | [Can ChatGPT Assess Human Personalities? A General Evaluation Framework](https://aclanthology.org/2023.findings-emnlp.84/) |
| 2311 | Dorner et al. | SoLaR @ NeurIPS | [Do personality tests generalize to large language models?](https://arxiv.org/abs/2311.05297) |
| 2310 | Wang et al. | arXiv | [InCharacter: Evaluating Personality Fidelity in Role-Playing Agents through Psychological Interviews](https://arxiv.org/abs/2310.17976) |
| 2309 | Jiang et al. | NeurIPS | [Evaluating and inducing personality in pre-trained language models](https://arxiv.org/abs/2206.07550) |
| 2307 | Pan et al. | arXiv | [Do LLMs Possess a Personality? Making the MBTI Test an Amazing Evaluation for Large Language Models](https://arxiv.org/abs/2307.16180) |
| 2307 | Fang et al. | ACL | [On Text-based Personality Computing: Challenges and Future Directions](https://aclanthology.org/2023.findings-acl.691/) |
| 2307 | Ji et al. | arXiv | [Is ChatGPT a Good Personality Recognizer? A Preliminary Study](https://arxiv.org/abs/2307.03952) |
| 2305 | Jiang et al. | arXiv | [Personallm: Investigating the ability of large language models to express big five personality traits](https://arxiv.org/abs/2305.02547) |
๐ฑ How to contribute
:sparkles: Welcome to contribute to this reading list via :memo: [Issues](https://github.com/MiuLab/PersonaLLM-Survey/issues) using the following format.
| Date | Authors | Venue | Paper |
|:-----:|:---------------:|:-----------:|:----------------------------------------------------------------------------------------------------------------------------|
| 1706 | Vaswani, et al | NeurIPS | [Attention Is All You Need](https://proceedings.neurips.cc/paper_files/paper/2017/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf) |