16 citations · 49 across the 17 of their papers we have counts for
17 papers
Generative Models Enhanced by Sequence Labelling and Aspect-Code Switching Improve Cross-lingual Aspect-Based Sentiment Analysis
Jakub Šmíd, Pavel Přibáň, Pavel Král
Cross-lingual aspect-based sentiment analysis (ABSA) transfers knowledge from a source language with annotated data to a target language, enabling fine-grained sentiment analysis w…
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…
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…
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…
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…
Large Language Models for Summarizing Czech Historical Documents and Beyond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…
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…
UWBa at SemEval-2025 Task 7: Multilingual and Crosslingual Fact-Checked Claim Retrieval
Ladislav Lenc, Daniel Cífka, Jiří Martínek +2
This paper presents a zero-shot system for fact-checked claim retrieval. We employed several state-of-the-art large language models to obtain text embeddings. The models were then…
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…
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…
Few-shot Cross-lingual Aspect-Based Sentiment Analysis with Sequence-to-Sequence Models
Jakub Šmíd, Pavel Přibáň, Pavel Král
Aspect-based sentiment analysis (ABSA) has received substantial attention in English, yet challenges remain for low-resource languages due to the scarcity of labelled data. Current…
Large Language Models for Czech Aspect-Based Sentiment Analysis
Jakub Šmíd, Pavel Přibáň, Pavel Král
Aspect-based sentiment analysis (ABSA) is a fine-grained sentiment analysis task that aims to identify sentiment toward specific aspects of an entity. While large language models (…
Linear Transformations for Cross-lingual Sentiment Analysis
Pavel Přibáň, Jakub Šmíd, Adam Mištera +1
This paper deals with cross-lingual sentiment analysis in Czech, English and French languages. We perform zero-shot cross-lingual classification using five linear transformations c…