Are the Multilingual Models Better? Improving Czech Sentiment with Transformers
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 Czech language on three sentiment polarity datasets. We fine-tune and perform experiments with five multilingual and three monolingual models. We compare the monolingual and multilingual models' performance, including comparison with the older approach based on recurrent neural networks. Furthermore, we test the multilingual models and their ability to transfer knowledge from English to Czech (and vice versa) with zero-shot cross-lingual classification. Our experiments show that the huge multilingual models can overcome the performance of the monolingual models. They are also able to detect polarity in another language without any training data, with performance not worse than 4.4 % compared to state-of-the-art monolingual trained models. Moreover, we achieved new state-of-the-art results on all three datasets.
Code (1)
Similar Papers 제목 키워드 기반
Comparison of Czech Transformers on Text Classification Tasks
In this paper, we present our progress in pre-training monolingual Transformers for Czech and contribute to the research community by releasing our models for public. The need for such models emerged from our effort to e…
Classificationtext-classificationText ClassificationLarge Language Models for Czech Aspect-Based Sentiment Analysis
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 (LLMs) have shown strong performance in v…
Sentiment AnalysisExtending Czech Aspect-Based Sentiment Analysis with Opinion Terms: Dataset and LLM Benchmarks
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 three distinct ABSA tasks involving opinio…
Sentiment AnalysisFine-tuning multilingual language models in Twitter/X sentiment analysis: a study on Eastern-European V4 languages
The aspect-based sentiment analysis (ABSA) is a standard NLP task with numerous approaches and benchmarks, where large language models (LLM) represent the current state-of-the-art. We focus on ABSA subtasks based on Twit…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)In-Context LearningSentiment AnalysisPrompt-Based Approach for Czech Sentiment Analysis
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…
Sentiment AnalysisFew-Shot Learning