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- URN zum Zitieren dieses Dokuments:
- urn:nbn:de:bvb:355-epub-784799
- DOI zum Zitieren dieses Dokuments:
- 10.5283/epub.78479
Zusammenfassung
This study explores the use of fine-tuned open source large language models (LLMs) for Aspect-based Sentiment Analysis (ABSA), comparing their performance with state-of-the-art (SOTA) methods on English and German datasets with focus on low-resource scenarios. Results on the four ABSA subtasks Aspect Category Detection (ACD), Aspect Category Sentiment Analysis (ACSA), End-To-End-ABSA (E2E), and ...
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