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Learning Adaptive Parallel Reasoning with Language Models
Adaptive Parallel Reasoning (APR) enhances language model reasoning by combining serialized and parallel computations, improving performance, scalability, and accuracy through end-to-end reinforcement learning without predefined structures.
https://arxiv.org/abs//2504.15466
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
Adaptive Parallel Reasoning (APR) enhances language model reasoning by combining serialized and parallel computations, improving performance, scalability, and accuracy through end-to-end reinforcement learning without predefined structures.
https://arxiv.org/abs//2504.15466
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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