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This study investigates transformers' search capabilities using graph connectivity, revealing that while they can learn to search, performance declines with larger graphs, unaffected by model size or in-context learning.
https://arxiv.org/abs//2412.04703
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
This study investigates transformers' search capabilities using graph connectivity, revealing that while they can learn to search, performance declines with larger graphs, unaffected by model size or in-context learning.
https://arxiv.org/abs//2412.04703
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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