6 papers
Evaluating Pluralism in LLMs through Latent Perspectives
Laura Majer, Jan Å najder, Martin Tutek
The growing need to represent diverse perspectives has increased interest in pluralistic LLM generation. Although difficult to operationalize, identifying perspectives expressed in…
Context Parametrization with Compositional Adapters
Josip JukiÄ, Martin Tutek, Jan Å najder
Large language models (LLMs) often seamlessly adapt to new tasks through in-context learning (ICL) or supervised fine-tuning (SFT). However, ICL is inefficient when handling many d…
Disentangling Latent Shifts of In-Context Learning with Weak Supervision
Josip JukiÄ, Jan Å najder
In-context learning (ICL) enables large language models to perform few-shot learning by conditioning on labeled examples in the prompt. Despite its flexibility, ICL suffers from in…
What Makes You CLIC: Detection of Croatian Clickbait Headlines
Marija AnÄeliÄ, Dominik Å ipek, Laura Majer +1
Online news outlets operate predominantly on an advertising-based revenue model, compelling journalists to create headlines that are often scandalous, intriguing, and provocative -…
LLMs for Targeted Sentiment in News Headlines: Exploring the Descriptive-Prescriptive Dilemma
Jana Juroš, Laura Majer, Jan Šnajder
News headlines often evoke sentiment by intentionally portraying entities in particular ways, making targeted sentiment analysis (TSA) of headlines a worthwhile but difficult task.…
Claim Check-Worthiness Detection: How Well do LLMs Grasp Annotation Guidelines?
Laura Majer, Jan Å najder
The increasing threat of disinformation calls for automating parts of the fact-checking pipeline. Identifying text segments requiring fact-checking is known as claim detection (CD)…