Summary of Assisted Debate Builder with Large Language Models, by Elliot Faugier et al.
Assisted Debate Builder with Large Language Models
by Elliot Faugier, Frédéric Armetta, Angela Bonifati, Bruno Yun
First submitted to arxiv on: 14 May 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| 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 paper introduces ADBL2, a tool that leverages the capabilities of large language models to build assisted debates. ADBL2 uses relation-based argument mining to verify pre-established relations and create new arguments. The tool is highly modular and can work with various open-source large language models as plugins. As a by-product, the paper also provides a fine-tuned Mistral-7B model for relation-based argument mining, which outperforms existing approaches with an F1-score of 90.59% across all domains. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The tool is based on the capability of large language models to generalize and perform relation-based argument mining in various domains. It is designed to assist in the verification of pre-established relations and create new arguments. The paper also provides a fine-tuned Mistral-7B model for relation-based argument mining, which can be used with ADBL2. |
Keywords
* Artificial intelligence * F1 score
