April 19, 2024, 4:47 a.m. | Nicolay Rusnachenko, Anton Golubev, Natalia Loukachevitch

cs.CL updates on arXiv.org arxiv.org

arXiv:2404.12342v1 Announce Type: new
Abstract: In this paper we investigate the use of decoder-based generative transformers for extracting sentiment towards the named entities in Russian news articles. We study sentiment analysis capabilities of instruction-tuned large language models (LLMs). We consider the dataset of RuSentNE-2023 in our study. The first group of experiments was aimed at the evaluation of zero-shot capabilities of LLMs with closed and open transparencies. The second covers the fine-tuning of Flan-T5 using the "chain-of-thought" (CoT) three-hop reasoning …

analysis arxiv cs.cl language language models large language large language models sentiment sentiment analysis type

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