Summary of Debate-to-write: a Persona-driven Multi-agent Framework For Diverse Argument Generation, by Zhe Hu et al.
Debate-to-Write: A Persona-Driven Multi-Agent Framework for Diverse Argument Generation
by Zhe Hu, Hou Pong Chan, Jing Li, Yu Yin
First submitted to arxiv on: 28 Jun 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This AI research paper proposes a novel approach to generating persuasive arguments, leveraging multi-agent frameworks inspired by human debates. Current language models struggle with limited output diversity and coherence due to their autoregressive nature. The proposed persona-based framework assigns agents unique perspectives and enables fluid, nonlinear development of ideas through collaborative debate. The results demonstrate that this approach can generate more diverse and persuasive arguments through both automatic and human evaluations. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine trying to convince someone of a point you’re passionate about. You’d want to present your argument in the most effective way possible, right? This paper is all about developing AI systems that can do just that – create compelling arguments that people will listen to. Right now, AI language models are pretty good at generating text, but they often sound robotic and don’t really “think” through their ideas. The researchers behind this project want to change that by creating a system that lets multiple “agents” work together to come up with the best argument possible. They tested it on writing essays, and the results show that this approach can create more diverse and persuasive arguments than traditional AI methods. |
Keywords
» Artificial intelligence » Autoregressive
