Existing neural information retrieval (IR) models have often been studied in homogeneous
and narrow settings, which has considerably limited insights into their out-of-distribution …

Argument mining is the automatic identification and extraction of the structure of inference
and reasoning expressed as arguments presented in natural language. Understanding …

Abstract Argumentation mining is a rising subject in the computational linguistics domain
focusing on extracting structured arguments from natural text, often from unstructured or …

Argument mining is a core technology for automating argument search in large document
collections. Despite its usefulness for this task, most current approaches to argument mining …

Identifying the quality of free-text arguments has become an important task in the rapidly
expanding field of computational argumentation. In this work, we explore the challenging …

This paper is a condensed report on Touché: the first shared task on argument retrieval that
was held at CLEF 2020. With the goal to create a collaborative platform for research in …

Generating a concise summary from a large collection of arguments on a given topic is an
intriguing yet understudied problem. We propose to represent such summaries as a small …

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 …

One key consequence of the information revolution is a significant increase and a
contamination of our information supply. The practice of fact checking won't suffice to …

Given any argument on any controversial topic, how to counter it? This question implies the
challenging retrieval task of finding the best counterargument. Since prior knowledge of a …