16 citations · 40 across the 12 of their papers we have counts for
13 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…
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…
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…
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…
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…
Czech Dataset for Cross-lingual Subjectivity Classification
Pavel Přibáň, Josef Steinberger
In this paper, we introduce a new Czech subjectivity dataset of 10k manually annotated subjective and objective sentences from movie reviews and descriptions. Our prime motivation…
Are the Multilingual Models Better? Improving Czech Sentiment with Transformers
Pavel Přibáň, Josef Steinberger
In this paper, we aim at improving Czech sentiment with transformer-based models and their multilingual versions. More concretely, we study the task of polarity detection for the C…