Papers with argumentative reasoning

3 papers
Evaluating the Performance of Large Language Models via Debates (2025.findings-naacl)

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Challenge: Large Language Models (LLMs) are evolving and impacting various fields . current methods for evaluation are based on fixed, domain-specific questions or rely on human input, making them unscalable.
Approach: They propose a benchmarking framework based on debates between LLMs, judged by another LLM.
Outcome: The proposed framework achieves rankings that align closely with popular rankings based on human input eliminating the need for costly crowdsourcing.
Natural Language Reasoning in Large Language Models: Analysis and Evaluation (2025.findings-acl)

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Challenge: Argumentative reasoning presents unique challenges due to its reliance on context, implicit assumptions, and value judgments.
Approach: They propose a large-scale evaluation of LLMs' unconstrained natural language reasoning capabilities . they formalise a new strategy designed to evaluate argumentative reasoning in LLM .
Outcome: The proposed model performs better on a range of reasoning tasks than other models.
Beyond Recognising Entailment: Formalising Natural Language Inference from an Argumentative Perspective (2024.acl-long)

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Challenge: Existing methods for recognizing textual entailment lack a standardized definition of inference, making it difficult to compare methods trained on different datasets.
Approach: They propose a rigorous approach to align entailment recognition with argumentation theory by using a tool to assist humans in annotating arguments according to the PTA.
Outcome: The proposed model is based on a human-trained dataset and provides insights into non-expert annotator training.

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