We fine-tune large language models to write natural language critiques (natural language
critical comments) using behavioral cloning. On a topic-based summarization task, critiques …

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 …

In the last decade, the field of argument mining has grown notably. However, only relatively
few studies have investigated argumentation in social media and specifically on Twitter …

Social media collect and spread on the Web personal opinions, facts, fake news and all kind
of information users may be interested in. Applying argument mining methods to such …

Social media contains unfiltered and unique information, which is potentially of great value,
but, in the case of misinformation, can also do great harm. With regards to biomedical topics …

Identifying the main claims occurring across texts is important for large-scale argumentation
mining from social media. However, the claims that users make are often unclear and build …

The problem of understanding the stream of messages exchanged on social media such as
Facebook and Twitter is becoming a major challenge for automated systems. The …

Notwithstanding the increasing role Twitter plays in modern political and social discourse,
resources built for conducting argument mining on tweets remain limited. In this paper, we …

This study introduces the first hybrid annotation model for Arabic argumentation debate
corpus. It aims to analyze Arabic argumentation structure in this competitive debate corpus …