PARIKSHA: A Scalable, Democratic, Transparent Evaluation Platform for Assessing Indic Large Language Models
Article Status
Published
Authors/contributors
- Watts, Ishaan (Author)
- Gumma, Varun (Author)
- Yadavalli, Aditya (Author)
- Seshadri, Vivek (Author)
- Manohar, Swami (Author)
- Sitaram, Sunayana (Author)
Title
PARIKSHA: A Scalable, Democratic, Transparent Evaluation Platform for Assessing Indic Large Language Models
Abstract
Evaluation of multilingual Large Language Models (LLMs) is challenging due to a variety of factors – the lack of benchmarks with sufficient linguistic diversity, contamination of popular benchmarks into LLM pre-training data and the lack of local, cultural nuances in translated benchmarks. Hence, it is difficult to do extensive evaluation of LLMs in the multilingual […]
Date
May 1st, 2024
Language
en-US
Short Title
PARIKSHA
Accessed
13/06/2024, 08:57
Library Catalogue
Citation
Watts, I., Gumma, V., Yadavalli, A., Seshadri, V., Manohar, S., & Sitaram, S. (2024). PARIKSHA: A Scalable, Democratic, Transparent Evaluation Platform for Assessing Indic Large Language Models. https://www.microsoft.com/en-us/research/publication/pariksha-a-scalable-democratic-transparent-evaluation-platform-for-assessing-indic-large-language-models/
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