11 citations · 36 across the 18 of their papers we have counts for
7 papers · 1 filter
Embedding Models for Stance-Aware Argument Retrieval
Angelo Sparacino, Francesca Toni, Adam Dejl
In computational argumentation, obtaining arguments that explicitly support or attack given claims is a critical precursor to downstream reasoning tasks. When these supporting and…
A Theory of Post-hoc Debate Judgement
Xiang Yin, Adam Dejl, Antonio Rago +2
Debates have recently emerged as a useful methodology for agentic AI to improve performance as well as to aid explainability and user engagement. For example, LLM-empowered agents…
When Do Explanations Help In-Context Learning? A Comparative Study of Natural Language Explanation Types and Faithfulness
Mahdi Dhaini, Adam Dejl, Juraj Vladika +3
Natural language explanations (NLEs) are increasingly used as inputs, for example, as few-shot rationales that influence model behavior in in-context learning (ICL). However, it re…
Neurosymbolic Learning for Inference-Time Argumentation
Gabriel Freedman, Adam Dejl, Adam Gould +4
Claim verification is an important problem in high-stakes settings, including health and finance. When information underpinning claims is incomplete or conflicting, uncertain answe…
Argumentation for Explainable and Globally Contestable Decision Support with LLMs
Adam Dejl, Matthew Williams, Francesca Toni
Large language models (LLMs) exhibit strong general capabilities, but their deployment in high-stakes domains is hindered by their opacity and unpredictability. Recent work has tak…
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…
EvalSense: A Framework for Domain-Specific LLM (Meta-)Evaluation
Adam Dejl, Jonathan Pearson
Robust and comprehensive evaluation of large language models (LLMs) is essential for identifying effective LLM system configurations and mitigating risks associated with deploying…