Evaluating Generative Artificial Intelligence on Multilingual Sentiment Analysis

Abstract

This study shows that natural language processing (NLP), large language models (LLM), and generative Artificial Intelligence are becoming the most important. LLM is considered essential for many NLP tasks, including question-answering, classification, interpretation, and writing. New LLMs must be able to analyze and create documents in different languages as they know how to train training materials in different languages such as ChatGPT, BLOOMZ, and others. Considering how frequently LLMs are used, it is critical to assess the effectiveness in multi-lingual environments. In a zero-shot context, the present generative models are still useful in producing text in Indian languages. On the other hand, generative models routinely outperform human quality-based evaluation when it comes to English language generation and Indian languages. LLMs are not meant to be used in a zero-shot manner in downstream applications due to poor generating performance.