Papers by Pranjal Chitale

1 papers
An Empirical Study of In-context Learning in LLMs for Machine Translation (2024.findings-acl)

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Challenge: Recent studies focus on optimizing translation quality, with limited attention to understanding specific aspects of ICL that influence the said quality.
Approach: They conduct the first of its kind, exhaustive study of in-context learning for machine translation (MT) they establish that ICL is primarily example-driven and not instruction-driven .
Outcome: The proposed model is based on examples and not instruction-driven learning.

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