10 citations · 16 across the 6 of their papers we have counts for
6 papers
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…
Retrieval- and Argumentation-Enhanced Multi-Agent LLMs for Judgmental Forecasting (Extended Version with Supplementary Material)
Deniz Gorur, Antonio Rago, Francesca Toni
Judgmental forecasting is the task of making predictions about future events based on human judgment. This task can be seen as a form of claim verification, where the claim corresp…
Argumentatively Coherent Judgmental Forecasting
Deniz Gorur, Antonio Rago, Francesca Toni
Judgmental forecasting employs human opinions to make predictions about future events, rather than exclusively historical data as in quantitative forecasting. When these opinions f…
Contestable AI needs Computational Argumentation
Francesco Leofante, Hamed Ayoobi, Adam Dejl +10
AI has become pervasive in recent years, but state-of-the-art approaches predominantly neglect the need for AI systems to be contestable. Instead, contestability is advocated by AI…
Argumentative Large Language Models for Explainable and Contestable Claim Verification
Gabriel Freedman, Adam Dejl, Deniz Gorur +3
The profusion of knowledge encoded in large language models (LLMs) and their ability to apply this knowledge zero-shot in a range of settings makes them promising candidates for us…
Can Large Language Models perform Relation-based Argument Mining?
Deniz Gorur, Antonio Rago, Francesca Toni
Argument mining (AM) is the process of automatically extracting arguments, their components and/or relations amongst arguments and components from text. As the number of platforms…