Chatbots are conversational software applications designed to interact dialectically with
users for a plethora of different purposes. Surprisingly, these colloquial agents have only …

Evaluating the quality of arguments is a crucial aspect of any system leveraging argument
mining. However, it is a challenge to obtain reliable and consistent annotations regarding …

To better analyze informal arguments on public forums, we propose the task of argument
explication, which makes explicit a text's argumentative structure and implicit reasoning by …

Despite the remarkable performance of Large Language Models (LLMs) in natural language
processing tasks, they still struggle with generating logically sound arguments, resulting in …

Competitive debate is a complex task of computational argumentation. Large Language
Models (LLMs) suffer from hallucinations and lack competitiveness in this field. To address …

The diversity of knowledge encoded in large language models (LLMs) and their ability to
apply this knowledge zero-shot in a range of settings makes them a promising candidate for …

Abstract Argumentation mining (AM) aims to detect the arguments and their inherent
relations from argumentative textual compositions. Generally, AM comprises three key …

There are two main barriers to using large language models (LLMs) in clinical reasoning.
Firstly, while LLMs exhibit significant promise in Natural Language Processing (NLP) tasks …

How can we effectively model arguments communicated in diverse environments? On the
one hand, there is a great opportunity with the abundance of digitized speech across …

End-to-end argumentation mining (AM) aims to extract the argumentation structure including
argumentation components and their argumentation relations from text. Recent …