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[QA] Uncovering Layer-Dependent Activation Sparsity Patterns in ReLU Transformers
The paper explores sparsity in ReLU Transformers, showing distinct layer-specific patterns and discussing implications for feature representations. Training dynamics drive "neuron death" rather than randomness.
https://arxiv.org/abs//2407.07848
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
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By Igor Melnyk
5
33 ratings
The paper explores sparsity in ReLU Transformers, showing distinct layer-specific patterns and discussing implications for feature representations. Training dynamics drive "neuron death" rather than randomness.
https://arxiv.org/abs//2407.07848
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
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