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The paper challenges the Linear Representation Hypothesis, showing that gated recurrent neural networks encode token sequences using magnitude rather than direction, suggesting broader interpretability in neural network research.
https://arxiv.org/abs//2408.10920
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
By Igor Melnyk5
33 ratings
The paper challenges the Linear Representation Hypothesis, showing that gated recurrent neural networks encode token sequences using magnitude rather than direction, suggesting broader interpretability in neural network research.
https://arxiv.org/abs//2408.10920
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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