This research investigates the Telugu language capabilities of two prominent large language models (LLMs): ChatGPT and Gemini. The study utilizes a set of 20 carefully designed questions to evaluate the LLMs' understanding of Telugu grammar, vocabulary, common phrases, and their ability to perform tasks within the language.
The analysis reveals that while both models possess a functional understanding of Telugu, Gemini demonstrates a slight edge in terms of grammatical accuracy, vocabulary breadth, and cultural awareness. Gemini excels in natural language generation tasks, showcasing its ability to generate coherent and contextually appropriate Telugu text. In contrast, ChatGPT exhibits a stronger performance in tasks requiring factual knowledge retrieval.
The findings suggest that the training data and architectural differences between the two LLMs may contribute to their varying strengths. Gemini's superior performance in creative tasks and cultural understanding could be attributed to a more diverse training corpus, including a wider range of Telugu text formats and cultural references. Conversely, ChatGPT's focus on factual knowledge retrieval may be a result of its training data prioritizing accuracy over creative expression.
The study highlights the importance of incorporating diverse text formats, cultural nuances, and natural language understanding capabilities during the development of multilingual LLMs. By addressing these areas, future research can contribute to the creation of LLMs that can seamlessly integrate with diverse language communities, fostering more inclusive and effective communication in the digital landscape.
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by Katikela Sre... o arxiv.org 05-01-2024
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