Prompt-Based Approach for Czech Sentiment Analysis
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Abstract (arXiv)
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 the aspect-based tasks simultaneously and demonstrate the superiority of our prompt-based approach over traditional fine-tuning. In addition, we conduct zero-shot and few-shot learning experiments for sentiment classification and show that prompting yields significantly better results with limited training examples compared to traditional fine-tuning. We also demonstrate that pre-training on data from the target domain can lead to significant improvements in a zero-shot scenario.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 19 of its 43 references that are in the map. First posted on arXiv 12 Aug 2025.
Builds on
19 of 43 references.
References · 19
- 2017Attention Is All You Needcited by 60,361
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
- 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893
- 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,935
- 2020mT5: A massively multilingual pre-trained text-to-text transformercited by 1,818
- 2020Making Pre-trained Language Models Better Few-shot Learnerscited by 1,256
- 2014Convolutional Neural Networks for Sentence Classificationcited by 1,127
- 2018Adafactor: Adaptive Learning Rates with Sublinear Memory Costcited by 905
- 2020It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learnerscited by 669
- 2017Beam Search Strategies for Neural Machine Translationcited by 232
- 2021Aspect Sentiment Quad Prediction as Paraphrase Generationcited by 100
7 more
- 2021RobeCzech: Czech RoBERTa, a monolingual contextualized language representation modelcited by 33
- 2016SentiHood: Targeted Aspect Based Sentiment Analysis Dataset for Urban Neighbourhoodscited by 32
- 2021Czert -- Czech BERT-like Model for Language Representationcited by 22
- 2021Comparison of Czech Transformers on Text Classification Taskscited by 10
- 2021Are the Multilingual Models Better? Improving Czech Sentiment with Transformerscited by 7
- 2022Czech Dataset for Cross-lingual Subjectivity Classificationcited by 5
- 2022Linear Transformations for Cross-lingual Sentiment Analysiscited by 2
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Citing papers per year: 2025: 1; 2026: 1.
2 papers.