2024
ACL
ACL 2024
Incorporating Syntax and Lexical Knowledge to Multilingual Sentiment Classification on Large Language Models
Abstract
AbstractThis paper exploits a sentiment extractor supported by syntactic and lexical resources to enhance multilingual sentiment classification solved through the generative approach, without retraining LLMs. By adding external information of words and phrases that have positive/negative polarities, the multilingual sentiment classification error was reduced by up to 33 points, and the combination of two approaches performed best especially in high-performing pairs of LLMs and languages.
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Interdisciplinary Bridge
— Artificial Intelligence and Deep Learning and Machine Learning and Natural Language Processing
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Keyword Pioneer
— multilingual sentiment classification
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Machine Learning > Application Areas > Domain Adaptation
Natural Language Processing > Understanding > Sentiment Analysis
Natural Language Processing > Applications > Sentiment Analysis
Deep Learning > Models > Large Language Models
Machine Learning > Learning Types > Deep Learning
Artificial Intelligence > Core AI > Multi-Modal Learning