DS@GT ARC at Touché: Large Language Models for Retrieval-Augmented Debate
We extend the DS@GT ARC working-note submission to the Touché 2025 Retrieval-Augmented Debate task. The task has two subtasks: generating the next utterance in a simulated debate, and evaluating debate responses according to the Gricean maxims of Quantity, Quality, Relation, and Manner. The DS@GT ARC submission consisted of six leading LLMs from three providers through a retrieval-augmented prompting pipeline. We summarize the results from the working paper and explore whether multi-LLM evaluator agreement is a reliable proxy for official evaluation performance. The analysis shows that frontier LLM systems are strong response generators, and as evaluators they agree strongly within model ...
| Authors | Anthony Miyaguchi, Conor Johnston |
|---|---|
| Primary category | cs.IR |
| Published | 8 August 2026 |
| Last updated at source | 8 August 2026 |
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