Inverse Scaling in Test-Time Compute
from Arxiv Papers Hosted by Igor Melnyk
The study reveals that increasing reasoning length in Large Reasoning Models can reduce accuracy, highlighting five failure modes and the need for diverse evaluation tasks to improve model performance. https://arxiv.org/abs//2507.14417 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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This episode was published on July 22, 2025.
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