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ChatGPT in Low-Resource Languages

Status: Completed

A semester-long undergraduate research program testing how well large language models actually work once you leave English. Each of the eight teams took a different low-resource or non-English language, from Urdu and Bengali to Korean, Russian, and Indonesian, and a different capability: chain-of-thought reasoning, sentiment analysis, question answering, named-entity recognition, or standardized-exam performance. The recurring finding, language after language, was that today's models grow sharply weaker, and less culturally grounded, the further a language sits from their English-heavy training data. Two of the teams took their work all the way to published benchmarks.

BibTeX