Argument Quality Assessment with Large Language Models: A Pairwise Bradley-Terry Approach
Large Language Models (LLMs) have demonstrated remarkable capabilities in tasks related to reasoning and judgment. However, assessing the quality of arguments requires a rigorous evaluation. We investigate the extent to which LLMs can effectively perform this task. We tested 12 open-weight LLMs of different sizes and families under zero-shot, few-shot, and chain-of-thought to approximate human pairwise comparisons of argument quality across three dimensions--logical, rhetorical, and dialectic--and used these comparisons in a Bradley-Terry model to infer latent strength scores and derive a ranking of arguments. Our insights show that LLMs have promising but moderate correlation with human ...
| Authors | Nicolás Benjamín Ocampo, Agnes Paullate Nyiranziza, Davide Ceolin |
|---|---|
| Primary category | cs.CL |
| Published | 27 May 2026 |
| Last updated at source | 31 August 2026 |
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