Debate-to-Write: A Persona-Driven Multi-Agent Framework for Diverse Argument Generation

Fuente: arXiv
Enregistré dans:
Détails bibliographiques
Auteurs principaux: Hu, Zhe, Chan, Hou Pong, Li, Jing, Yin, Yu
Format: Preprint
Publié: 2024
Sujets:
Accès en ligne:
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866909447313424384
author Hu, Zhe
Chan, Hou Pong
Li, Jing
Yin, Yu
author_facet Hu, Zhe
Chan, Hou Pong
Li, Jing
Yin, Yu
contents Writing persuasive arguments is a challenging task for both humans and machines. It entails incorporating high-level beliefs from various perspectives on the topic, along with deliberate reasoning and planning to construct a coherent narrative. Current language models often generate surface tokens autoregressively, lacking explicit integration of these underlying controls, resulting in limited output diversity and coherence. In this work, we propose a persona-based multi-agent framework for argument writing. Inspired by the human debate, we first assign each agent a persona representing its high-level beliefs from a unique perspective, and then design an agent interaction process so that the agents can collaboratively debate and discuss the idea to form an overall plan for argument writing. Such debate process enables fluid and nonlinear development of ideas. We evaluate our framework on argumentative essay writing. The results show that our framework can generate more diverse and persuasive arguments through both automatic and human evaluations.
format Preprint
id arxiv_https___arxiv_org_abs_2406_19643
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Debate-to-Write: A Persona-Driven Multi-Agent Framework for Diverse Argument Generation
Hu, Zhe
Chan, Hou Pong
Li, Jing
Yin, Yu
Computation and Language
Artificial Intelligence
Writing persuasive arguments is a challenging task for both humans and machines. It entails incorporating high-level beliefs from various perspectives on the topic, along with deliberate reasoning and planning to construct a coherent narrative. Current language models often generate surface tokens autoregressively, lacking explicit integration of these underlying controls, resulting in limited output diversity and coherence. In this work, we propose a persona-based multi-agent framework for argument writing. Inspired by the human debate, we first assign each agent a persona representing its high-level beliefs from a unique perspective, and then design an agent interaction process so that the agents can collaboratively debate and discuss the idea to form an overall plan for argument writing. Such debate process enables fluid and nonlinear development of ideas. We evaluate our framework on argumentative essay writing. The results show that our framework can generate more diverse and persuasive arguments through both automatic and human evaluations.
title Debate-to-Write: A Persona-Driven Multi-Agent Framework for Diverse Argument Generation
topic Computation and Language
Artificial Intelligence
url https://arxiv.org/abs/2406.19643