MATA (māta): Mindful Assessment of the Telugu Abilities of Large Language Models

• URL: http://arxiv.org/abs/2508.13526v1
• Date: Tue, 19 Aug 2025 05:33:57 GMT
• Title: MATA (māta): Mindful Assessment of the Telugu Abilities of Large Language Models
• Authors: Chalamalasetti Kranti, Sowmya Vajjala,
• Abstract summary: MATA is a novel evaluation dataset to assess the ability of Large Language Models (LLMs) in Telugu language.<n>We evaluate 11 open-weight and closed-source LLMs on our dataset and present a fine-grained analysis of their performance.
• Score: 2.7624021966289605
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: In this paper, we introduce MATA, a novel evaluation dataset to assess the ability of Large Language Models (LLMs) in Telugu language, comprising 729 carefully curated multiple-choice and open-ended questions that span diverse linguistic dimensions. We evaluate 11 open-weight and closed-source LLMs on our dataset and present a fine-grained analysis of their performance. Further, we empirically show how LLMs rely on superficial heuristics such as answer position and distractor patterns for multiple-choice questions. Finally, we also compare LLM-as-a-judge evaluation with human evaluation for open-ended questions and draw some conclusions on its reliability in a low-resource language. We argue that such fine-grained evaluation is essential for understanding model limitations and can inform the development of more linguistically capable LLMs, while also serving as a foundation for future research in Telugu NLP.

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