2 citations · 4 across the 8 of their papers we have counts for
8 papers
Evaluating Pluralism in LLMs through Latent Perspectives
Laura Majer, Jan Šnajder, 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 Jukić, Martin Tutek, Jan Šnajder
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…
What Makes You CLIC: Detection of Croatian Clickbait Headlines
Marija Anđelić, Dominik Šipek, 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 -…
Disentangling Latent Shifts of In-Context Learning with Weak Supervision
Josip Jukić, Jan Šnajder
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…
Claim Check-Worthiness Detection: How Well do LLMs Grasp Annotation Guidelines?
Laura Majer, Jan Šnajder
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)…
From Robustness to Improved Generalization and Calibration in Pre-trained Language Models
Josip Jukić, Jan Šnajder
Enhancing generalization and uncertainty quantification in pre-trained language models (PLMs) is crucial for their effectiveness and reliability. Building on machine learning resea…
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.…
Data Augmentation for Neural NLP
Domagoj Pluščec, Jan Šnajder
Data scarcity is a problem that occurs in languages and tasks where we do not have large amounts of labeled data but want to use state-of-the-art models. Such models are often deep…