Advancing Sentiment Analysis in Serbian Literature: A Zero and Few-Shot Learning Approach Using the Mistral Model

The paper presented at The Sixth International Conference on Computational Linguistics in Bulgaria (CLIB 2024).

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-09-01
DOI
https://doi.org/10.5281/zenodo.13973647
Primary Topic
Sentiment Analysis and Opinion Mining
Type
article
Field-Weighted Citation Impact
0.00
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article

Advancing Sentiment Analysis in Serbian Literature: A Zero and Few-Shot Learning Approach Using the Mistral Model

Zenodo (CERN European Organization for Nuclear Research)
Sentiment Analysis and Opinion Mining
article

Advancing Sentiment Analysis in Serbian Literature: A Zero and Few-Shot Learning Approach Using the Mistral Model

article en

Abstract

The paper presented at The Sixth International Conference on Computational Linguistics in Bulgaria (CLIB 2024).

Zenodo (CERN European Organization for Nuclear Research)
University of Belgrade (RS), University of Belgrade – Faculty of Philology, University of Belgrade - Faculty of Mining and Geology
Quality Education
Openalex Percentile: Top 68%
Sentiment Analysis and Opinion Mining
DOIOpen Access PDFOpenAlex
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Advancing Sentiment Analysis in Serbian Literature: A Zero and Few-Shot Learning Approach Using the Mistral Model · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS