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Study: LLMs sound persuasive but argue poorly in dialogues

A new study published on arXiv introduces Persuasio, a platform designed to evaluate the persuasive dialogue capabilities of large language models (LLMs). The research generated 192 debates on a UK political topic, pitting humans against LLMs. Findings indicate a significant gap between LLMs' perceived persuasiveness and their actual argumentative strength, with humans remaining competitive in formal adjudication despite LLMs dominating subjective rankings. AI

IMPACT Highlights a potential disconnect between LLM fluency and logical reasoning, suggesting current models may not be as adept at formal argumentation as they appear.

RANK_REASON Research paper published on arXiv detailing a new evaluation method for LLMs. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Study: LLMs sound persuasive but argue poorly in dialogues

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Research paper published on arXiv detailing a new evaluation method for LLMs. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Jordan Robinson, Angus R. Williams, Katie Atkinson, Anthony G. Cohn ·

    Evaluating the Capabilities of LLMs for Persuasive Dialogue

    arXiv:2608.29738v1 Announce Type: new Abstract: Large language models (LLMs) can generate apparently highly persuasive text, but does sounding persuasive mean arguing well? We introduce \textsc{Persuasio}, a multi-agent dialogue platform grounded in a formal argumentation-based t…