16 citations · 30 across the 9 of their papers we have counts for
9 papers
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…
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…
Prompt-Based Approach for Czech Sentiment Analysis
Jakub Šmíd, Pavel Přibáň
This paper introduces the first prompt-based methods for aspect-based sentiment analysis and sentiment classification in Czech. We employ the sequence-to-sequence models to solve t…
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…
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…
Czech Dataset for Complex Aspect-Based Sentiment Analysis Tasks
Jakub Šmíd, Pavel Přibáň, Ondřej Pražák +1
In this paper, we introduce a novel Czech dataset for aspect-based sentiment analysis (ABSA), which consists of 3.1K manually annotated reviews from the restaurant domain. The data…