[Submitted on 13 Jan 2024 (
[v1](https://arxiv.org/abs/2401.07013v1)), last revised 9 Nov 2024 (this version, v2)]# Title:Knowledge Distillation of Black-Box Large Language Models
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Abstract:Given the exceptional performance of proprietary large language models (LLMs) like GPT-4, recent research has increasingly focused on boosting the capabilities of smaller models through knowledge distillation (KD) from these powerful yet black-box teachers. While leveraging the high-quality outputs of these teachers is advantageous, the inaccessibility of their internal states often limits effective knowledge transfer. To overcome this limitation, we introduce Proxy-KD, a novel method that uses a proxy model to facilitate the efficient transfer of knowledge from black-box LLMs to smaller models. Our experiments show that Proxy-KD not only enhances the performance of KD from black-box teacher models but also surpasses traditional white-box KD techniques.~This approach presents a compelling new avenue for distilling knowledge from advanced LLMs.
Submission history #
From: Hongzhan Chen [[view email](/show-email/794667b0/2401.07013)]
**Sat, 13 Jan 2024 08:43:32 UTC (359 KB)**
[[v1]](/abs/2401.07013v1)**[v2]** Sat, 9 Nov 2024 01:35:32 UTC (8,288 KB)
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