Recent advancements in Large Language Models (LLMs) have significantly influenced the
landscape of language and speech research. Despite this progress, these models lack …

The five editions of the CheckThat! lab so far have focused on the main tasks of the
information verification pipeline: check-worthiness, evidence retrieval and pairing, and …

We describe the outcome of the 2023 edition of the CheckThat! Lab at CLEF. We focus on
subjectivity (Task 2), which has been proposed for the first time. It aims at fostering the …

Detecting subjectivity in news sentences is crucial for identifying media bias, enhancing
credibility, and combating misinformation by flagging opinion-based content. It provides …

We develop novel annotation guidelines for sentence-level subjectivity detection, which are
not limited to language-specific cues. We use our guidelines to collect NewsSD-ENG, a …

We explore the use of residual networks and neural attention for multiple argument mining
tasks. We propose a residual architecture that exploits attention, multi-task learning, and …

We present an overview of Task 2 of the seventh edition of the CheckThat! lab at the 2024
iteration of the Conference and Labs of the Evaluation Forum (CLEF). The task focuses on …

Defining subjectivity indicators without relying on domain-specific assumptions or incurring
interpretation biases is a well-known challenge. To account for these limitations, recent work …

The problem of subjectivity detection is often approached as a preparatory binary task for
sentiment analysis, despite the fact that theoretically subjectivity is often defined as a matter …

Sentiment analysis on legal cases is an under-explored field. While traditionally applied in
marketing and customer review analysis, sentiment analysis can also be used on legal …