collaborators

7 papers

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Large Language Models for Summarizing Czech Historical Documents and Beyond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…

cs.CL2025

Cross-lingual Aspect-Based Sentiment Analysis: A Survey on Tasks, Approaches, and Challenges

Jakub Šmíd, Pavel Král

Aspect-based sentiment analysis (ABSA) is a fine-grained sentiment analysis task that focuses on understanding opinions at the aspect level, including sentiment towards specific as…

cs.CL2025

LACA: Improving Cross-lingual Aspect-Based Sentiment Analysis with LLM Data Augmentation

Jakub Šmíd, Pavel Přibáň, Pavel Král

Cross-lingual aspect-based sentiment analysis (ABSA) involves detailed sentiment analysis in a target language by transferring knowledge from a source language with available annot…

cs.CL2025

UWB at WASSA-2024 Shared Task 2: Cross-lingual Emotion Detection

Jakub Šmíd, Pavel Přibáň, Pavel Král

This paper presents our system built for the WASSA-2024 Cross-lingual Emotion Detection Shared Task. The task consists of two subtasks: first, to assess an emotion label from six p…

cs.CL2025

LLaMA-Based Models for Aspect-Based Sentiment Analysis

Jakub Šmíd, Pavel Přibáň, Pavel Král

While large language models (LLMs) show promise for various tasks, their performance in compound aspect-based sentiment analysis (ABSA) tasks lags behind fine-tuned models. However…