arXiv Computation and Language September 1, 2026 By Jordan Robinson, Angus R. Williams, Katie Atkinson, Anthony G. Cohn

Evaluating the Capabilities of LLMs for Persuasive Dialogue

Read the original on arXiv Computation and Language →

The paper introduces “Persuasio”, a multi‑agent dialogue platform that uses a formal argumentation theory to adjudicate winners in free‑text debates. Using this system, the authors generated 192 debates on a UK political topic involving humans and large language models (LLMs), and evaluated 22 interlocutors through automated adjudication and 9,702 crowdsourced pairwise judgments across 1,386 annotation instances. The results show a consistent decoupling between subjective persuasiveness—where LLMs dominate—and formal argumentative strength—where humans remain competitive, with multi‑agent and retrieval‑augmented variants widening this gap.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

Hugging Face Trending Papers

Jun 10

A Resource for Enthymeme Detection in Controversial Political Discourse

Enthymemes, arguments with unstated premises or conclusions, are pervasive in persuasive discourse, yet their annotation remains notoriously subjective. We present a resource of 1,482 tweets from politically controversial discourse, annotated by five annotators for the presence of enthymemes and their argument structure, designed to study label variation.

nlp

arXiv Computation and Language

Aug 24

ARGUS: Theory-of-Mind Guided Argument Generation with Strategy-Aware Planning and Knowledge Grounding

ARGUS is a new agent-based framework for persuasive argument generation that incorporates a Theory-of-Mind Reasoner to model audience beliefs and values. It uses a component-aware planner to break arguments into subtopics, assign rhetorical functions (logos, pathos, ethos, kairos), and guide evidence retrieval during planning. A refinement module iteratively addresses multi-dimensional weaknesses, and evaluations on three benchmarks show ARGUS outperforming strong baselines and effectively shifting resistant audience stances.

By Zhe Hu

llms agents benchmarks

arXiv Machine Learning

Aug 4

OpenDebateEvidence: A Massive-Scale Argument Mining and Summarization Dataset

arXiv:2406. 14657v4 Announce Type: replace-cross Abstract: We introduce OpenDebateEvidence, a comprehensive dataset for argument mining and summarization sourced from the American Competitive Debate community.

By Allen Roush, Yusuf Shabazz, Arvind Balaji, Peter Zhang, Stefano Mezza, Markus Zhang, Sanjay Basu, Sriram Vishwanath, Mehdi Fatemi, Ravid Shwartz-Ziv

llms nlp fine-tuning benchmarks

arXiv Computation and Language

3d ago

Persuasion Index: A Theory-Guided Framework for Persuasion Analysis

The paper introduces the Persuasion Index (PI), a taxonomy of 15 persuasion dimensions grounded in psychological and communication theories, implemented with 55 lexicon- and rule-based sub-features. PI is modular, allowing individual detectors to be swapped while preserving its theoretical framework. Evaluations on four English argumentative datasets show that PI provides a shared, lightweight feature space that captures meaningful predictive signals and reveals consistent dimension-level associations with persuasion outcomes, with variations across topics and stances.

By Liancheng Gong, Zhiyang Wang, Yiwei Xu, Julia Mendelsohn

robotics safety

arXiv AI

Jun 2

Argument Collapse: LLMs Flatten Long-Form Public Debate

arXiv:2606. 01736v1 Announce Type: cross Abstract: As LLMs are increasingly used to draft public-facing arguments, they may flatten public debate by repeatedly introducing the same polished, plausible arguments.

By Yekyung Kim, Yapei Chang, Chau Minh Pham, Mohit Iyyer

llms

arXiv AI

Jun 9

"I understand your perspective": LLM Persuasion and Sycophancy through the Lens of Communicative Action Theory

arXiv:2606. 08076v1 Announce Type: cross Abstract: Large Language Models (LLMs) can generate high-quality arguments, yet their ability to engage in nuanced and persuasive communicative actions remains largely unexplored.

By Esra D\"onmez, Agnieszka Falenska