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Knowledge Distillation of Black-Box Large Language Models (2024)

arxiv.org

June 28, 2026

2 min read

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52/100

Summary

Knowledge distillation (KD) enhances the performance of smaller models by transferring knowledge from proprietary large language models (LLMs) like GPT-4. This method aims to improve the capabilities of smaller models while utilizing the strengths of black-box teachers.

Key Takeaways

Proxy-KD is a novel method introduced for knowledge distillation from black-box large language models to smaller models.
Proxy-KD enhances the performance of knowledge distillation compared to traditional white-box techniques.
The method addresses the limitations of inaccessibility of internal states in proprietary large language models.
Research increasingly focuses on improving smaller models by leveraging the high-quality outputs of advanced black-box LLMs.

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