collaborators

15 papers

cs.CL2026

Large Language Models for Citation Function Classification

Daniel Vodička, Jakub Šmíd, Pavel Král +1

Citation function classification plays a crucial role in understanding the relationships between scientific publications and advancing bibliometric analysis. This study presents on…

cs.CL2026

Extending Czech Aspect-Based Sentiment Analysis with Opinion Terms: Dataset and LLM Benchmarks

Jakub Šmíd, Pavel Přibáň, Pavel Král

This paper introduces a novel Czech dataset in the restaurant domain for aspect-based sentiment analysis (ABSA), enriched with annotations of opinion terms. The dataset supports th…

cs.CL2025

Large Language Models for the Summarization of Czech Documents: From History to the Present

Václav Tran, Jakub Šmíd, Ladislav Lenc +2

Text summarization is the task of automatically condensing longer texts into shorter, coherent summaries while preserving the original meaning and key information. Although this ta…

cs.CL2025

Improving Generative Cross-lingual Aspect-Based Sentiment Analysis with Constrained Decoding

Jakub Šmíd, Pavel Přibáň, Pavel Král

While aspect-based sentiment analysis (ABSA) has made substantial progress, challenges remain for low-resource languages, which are often overlooked in favour of English. Current c…

cs.CL2025

Large Language Models for Summarizing Czech Historical Documents and Beyond

Václav Tran, Jakub Šmíd, Jiří Martínek +2

Text summarization is the task of shortening a larger body of text into a concise version while retaining its essential meaning and key information. While summarization has been si…

cs.CL2025

Advancing Cross-lingual Aspect-Based Sentiment Analysis with LLMs and Constrained Decoding for Sequence-to-Sequence Models

Jakub Šmíd, Pavel Přibáň, Pavel Král

Aspect-based sentiment analysis (ABSA) has made significant strides, yet challenges remain for low-resource languages due to the predominant focus on English. Current cross-lingual…