Hedged sampling, checklist-based one-pass selection (CHOPS), and cross-lingual MBR (X-MBR) improve multilingual LLM output quality when scaling from one to five samples.
The multilingual alignment prism: Aligning global and local preferences to reduce harm
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When Life Gives You Samples: The Benefits of Scaling up Inference Compute for Multilingual LLMs
Hedged sampling, checklist-based one-pass selection (CHOPS), and cross-lingual MBR (X-MBR) improve multilingual LLM output quality when scaling from one to five samples.