Large Language Models (LLMs) have taken Knowledge Representation--and the world--by
storm. This inflection point marks a shift from explicit knowledge representation to a renewed …

This paper studies the (often implicit) human values behind natural language arguments,
such as to have freedom of thought or to be broadminded. Values are commonly accepted …

Qualitative data analysis (QDA) is useful for identifying patterns, themes, and relationships
among data. In this paper, we propose a new method that uses large language models …

This paper is a condensed report on the second year of the Touché shared task on
argument retrieval held at CLEF 2021. With the goal to provide a collaborative platform for …

The study of argumentation is transversal to several research domains, from philosophy to
linguistics, from the law to computer science and artificial intelligence. In discourse analysis …

Background The COVID-19 pandemic raised novel challenges in communicating reliable,
continually changing health information to a broad and sometimes skeptical public …

When summarizing a collection of views, arguments or opinions on some topic, it is often
desirable not only to extract the most salient points, but also to quantify their prevalence …

In real-world scenarios, a text classification task often begins with a cold start, when labeled
data is scarce. In such cases, the common practice of fine-tuning pre-trained models, such …

Claim detection and verification are crucial for news understanding and have emerged as
promising technologies for mitigating misinformation and disinformation in the news …

Key Point Analysis (KPA) has been recently proposed for deriving fine-grained insights from
collections of textual comments. KPA extracts the main points in the data as a list of concise …