Papers by Simiao Li

1 papers
Multi-Granularity Semantic Revision for Large Language Model Distillation (2026.acl-long)

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Challenge: Existing methods for generating large language models rely on student-generated outputs, which introduce generation errors and misguide the distillation process.
Approach: They propose a multi-granularity semantic revision method for LLM distillation that corrects errors using teacher-generated tokens and re-generates the sequence to minimize errors.
Outcome: The proposed method reduces errors and misguides distillation on student models and improves consistency between teacher and student outputs.

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