Papers by Wei-Chi Wu

1 papers
No One Fits All: From Fixed Prompting to Learned Routing in Multilingual LLMs (2026.findings-acl)

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Challenge: Existing studies show that translation-based prompting is not universally optimal for multilingual LLMs.
Approach: They evaluate translation-based prompting across ten languages and four benchmarks . they propose a lightweight classifier that predicts whether native or translation- based prompts are optimal .
Outcome: The proposed classifiers achieve statistically significant improvements over fixed prompting strategies across ten languages and four benchmarks.

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