Sparse Logit Sampling: Accelerating Knowledge Distillation in LLMs

from Arxiv Papers · host Igor Melnyk

This paper introduces a novel method, Random Sampling Knowledge Distillation, which improves sparse knowledge distillation by providing unbiased teacher probability estimates, enhancing student model training efficiency and performance. https://arxiv.org/abs//2503.16870 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers

Episode metadata supplied by the publisher feed · Published Mar 24, 2025

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Sparse Logit Sampling: Accelerating Knowledge Distillation in LLMs

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