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cs.CL2026

ArgLLM-App: An Interactive System for Argumentative Reasoning with Large Language Models

Adam Dejl, Deniz Gorur, Francesca Toni

Argumentative LLMs (ArgLLMs) are an existing approach leveraging Large Language Models (LLMs) and computational argumentation for decision-making, with the aim of making the result…

cs.CL2026

Latent Debate: A Surrogate Framework for Interpreting LLM Thinking

Lihu Chen, Xiang Yin, Francesca Toni

Understanding the internal thinking process of Large Language Models (LLMs) and the cause of hallucinations remains a key challenge. To this end, we introduce latent debate, a nove…

cs.CL2025

Evaluating Uncertainty Quantification Methods in Argumentative Large Language Models

Kevin Zhou, Adam Dejl, Gabriel Freedman +3

Research in uncertainty quantification (UQ) for large language models (LLMs) is increasingly important towards guaranteeing the reliability of this groundbreaking technology. We ex…

cs.CL2025

Pub-Guard-LLM: Detecting Retracted Biomedical Articles with Reliable Explanations

Lihu Chen, Shuojie Fu, Gabriel Freedman +6

A significant and growing number of published scientific articles is found to involve fraudulent practices, posing a serious threat to the credibility and safety of research in fie…

cs.CL2025

MArgE: Meshing Argumentative Evidence from Multiple Large Language Models for Justifiable Claim Verification

Ming Pok Ng, Junqi Jiang, Gabriel Freedman +2

Leveraging outputs from multiple large language models (LLMs) is emerging as a method for harnessing their power across a wide range of tasks while mitigating their capacity for ma…