Synthetic translated data improves language models across twelve Indian languages

The authors release a 2.83-trillion-token corpus and multilingual evaluation suite, then show that combining synthetic and natural Indic text improves knowledge and reasoning over a public-data baseline.

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Abhinav Khattar (NVIDIA) · Aishwarya Chhabra (NVIDIA) · Ameya Velingker (NVIDIA) · Anusha Kamath (NVIDIA) · Brandon Norick (NVIDIA) · Kanishk Singla (NVIDIA) · +21 more
Research Digest··3 min read
Khattar et al.

The authors translated curated English documents into Indian languages with a GPU-accelerated pipeline designed to preserve technical content, formatting and links to source material.

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