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Changyi He

2 accepted papers

2025

DA-KD: Difficulty-Aware Knowledge Distillation for Efficient Large Language Models

ICML 2025poster

Although knowledge distillation (KD) is an effective approach to improve the performance of a smaller LLM (i.e., the student model) by transferring knowledge from a large LLM (i.e., the teacher model), it still suffers from high training cost. Existing LLM distillation methods ignore the difficulty…

Cited by 0SourcePDFScholar
2024

LLMCBench: Benchmarking Large Language Model Compression for Efficient Deployment

NeurIPS 2024spotlight

Although large language models (LLMs) have demonstrated their strong intelligence ability, the high demand for computation and storage hinders their practical application. To this end, many model compression techniques are proposed to increase the efficiency of LLMs. However, current researches only…