Steering CLIP's vision transformer with sparse autoencoders

from Arxiv Papers · host Igor Melnyk

This study explores sparse autoencoders in vision models, revealing unique processing patterns and enhancing steerability, leading to improved performance in vision disentanglement tasks and defense strategies. https://arxiv.org/abs//2504.08729 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 Apr 14, 2025

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Steering CLIP's vision transformer with sparse autoencoders

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