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Measuring AI Accountability Through Argumentation Analysis: Can Model Reasoning Withstand Scrutiny?

Paper recorded by Signals 4 on 2026-09-04 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-04 on arXiv · recorded by Signals 4 on 2026-09-07

Category: cs.CL · 自然语言处理 · first seen 2026-09-07

Abstract

AI oversight methods rely on ground truth for validation, but what constitutes appropriate AI behavior is contested. This leaves evaluation of moral reasoning in LLMs and debate-based oversight implicitly avoiding realistic ambiguity. We investigate an alternative standard designed to function despite such ambiguity: structural quality of the defence a model can mount for its verdicts in response

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#111 most recent of 186 cs.CL papers we have recorded · ↑ newer: Improving Language Identification for Code-Switched Utterances with In · ↓ older: TruthInsightBench: An Evidence-Grounded Benchmark for Automated Evalua
Cite this page: Measuring AI Accountability Through Argumentation Analysis: Can Model Reasoning Withstand Scrutiny?: the #111 most recent of 186 cs.CL papers we have recorded (as of 2026-09-04). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/measuring-ai-accountability-through-argumentation-analysis-can-model-reasoning-w.html
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