MiuLab/PersonaLLM-Survey

119

5 commits

updated Oct 11, 2024

See the code

README

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

Static Badge GitHub Repo stars GitHub last commit


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] :dart: We update the camera-ready version on arXiv. Click the link to check it out!
  • [2024.09.20] :confetti_ball: Excited to share that our paper is accepted at EMNLP 2024 Findings! Hooray :raised_hands:!
  • [2024.06.27] :fire: We update an 8-page version on arXiv.
  • [2024.06.04] :rocket: Our paper is now available on arXiv and the reading list on GitHub.

Table of Contents

๐Ÿ™†โ€โ™€๏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.


LLM role-playing

๐Ÿ’ผ Workshops

DateWorkshopWebsite Link
2405LLMAgent @ ICLRICLR 2024 Workshop on Large Language Model (LLM) Agents
2405Agent Workshop @ CMUCMU Agent Workshop 2024

๐ŸŒŽ Environments

๐Ÿ’ป Software Development

๐ŸŒ Web

๐ŸŽฎ Game

๐Ÿฅ Medical Application

๐Ÿง‘โ€โš–๏ธ LLM as Evaluators

๐Ÿ“ฆ General Framework

๐Ÿค– Interaction & Behaviors

๐Ÿ“Š Schemas

๐Ÿ‘ค Single-Agent
๐Ÿ‘ฅ Multi-Agent

๐Ÿ’ก Emergent Behaviors

๐Ÿ™†โ€โ™‚๏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.

LLM personalization

๐Ÿ’ผ Workshops & Competitions

๐Ÿ“Œ Tasks

๐Ÿ’ฌ Personalized Dialogue

๐Ÿ”ง ToD Modeling

LLMs Era

Comprehensive Paper List

Pre-LLMs Era

Comprehensive Paper List
๐Ÿ“ User Persona Modeling
Comprehensive Paper List

๐Ÿ›’ Recommendation System

Comprehensive Paper List

๐Ÿฉบ Personalized Healthcare

๐Ÿ“š Personalized Education

๐Ÿ› ๏ธ Methods

๐ŸŽ›๏ธ Fine-Tuning

๐Ÿ”— Retrieval Augmentation

โœ๏ธ Prompting

๐Ÿ“„ Vanilla Personalized Prompt
๐Ÿ”ฆ Retrieval-Augmented Personalized Prompt
๐Ÿ“‚ Profile-Augmented Prompt

๐Ÿง LLM Personality Evaluation

Comprehensive Paper List

๐ŸŒฑ How to contribute

:sparkles: Welcome to contribute to this reading list via :memo: Issues using the following format.

DateAuthorsVenuePaper
1706Vaswani, et alNeurIPSAttention Is All You Need

๐Ÿ”– Citation

๐Ÿ“š 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},
}

๐Ÿ–Œ๏ธ 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.)

MiuLab/PersonaLLM-Survey

119

5 commits

updated Oct 11, 2024

See the code

README

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

Static Badge GitHub Repo stars GitHub last commit


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] :dart: We update the camera-ready version on arXiv. Click the link to check it out!
  • [2024.09.20] :confetti_ball: Excited to share that our paper is accepted at EMNLP 2024 Findings! Hooray :raised_hands:!
  • [2024.06.27] :fire: We update an 8-page version on arXiv.
  • [2024.06.04] :rocket: Our paper is now available on arXiv and the reading list on GitHub.

Table of Contents

๐Ÿ™†โ€โ™€๏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.


LLM role-playing

๐Ÿ’ผ Workshops

DateWorkshopWebsite Link
2405LLMAgent @ ICLRICLR 2024 Workshop on Large Language Model (LLM) Agents
2405Agent Workshop @ CMUCMU Agent Workshop 2024

๐ŸŒŽ Environments

๐Ÿ’ป Software Development

๐ŸŒ Web

๐ŸŽฎ Game

๐Ÿฅ Medical Application

๐Ÿง‘โ€โš–๏ธ LLM as Evaluators

๐Ÿ“ฆ General Framework

๐Ÿค– Interaction & Behaviors

๐Ÿ“Š Schemas

๐Ÿ‘ค Single-Agent
๐Ÿ‘ฅ Multi-Agent

๐Ÿ’ก Emergent Behaviors

๐Ÿ™†โ€โ™‚๏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.

LLM personalization

๐Ÿ’ผ Workshops & Competitions

๐Ÿ“Œ Tasks

๐Ÿ’ฌ Personalized Dialogue

๐Ÿ”ง ToD Modeling

LLMs Era

Comprehensive Paper List

Pre-LLMs Era

Comprehensive Paper List
๐Ÿ“ User Persona Modeling
Comprehensive Paper List

๐Ÿ›’ Recommendation System

Comprehensive Paper List

๐Ÿฉบ Personalized Healthcare

๐Ÿ“š Personalized Education

๐Ÿ› ๏ธ Methods

๐ŸŽ›๏ธ Fine-Tuning

๐Ÿ”— Retrieval Augmentation

โœ๏ธ Prompting

๐Ÿ“„ Vanilla Personalized Prompt
๐Ÿ”ฆ Retrieval-Augmented Personalized Prompt
๐Ÿ“‚ Profile-Augmented Prompt

๐Ÿง LLM Personality Evaluation

Comprehensive Paper List

๐ŸŒฑ How to contribute

:sparkles: Welcome to contribute to this reading list via :memo: Issues using the following format.

DateAuthorsVenuePaper
1706Vaswani, et alNeurIPSAttention Is All You Need

๐Ÿ”– Citation

๐Ÿ“š 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},
}

๐Ÿ–Œ๏ธ 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.)