Entropy-Guided Attention for Private LLMs

from Arxiv Papers · host Igor Melnyk

This paper addresses privacy concerns in proprietary language models by optimizing transformer architectures for private inference, focusing on the role of nonlinearities and introducing entropy-guided mechanisms for improved performance. https://arxiv.org/abs//2501.03489 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 Jan 8, 2025

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Entropy-Guided Attention for Private LLMs

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