The results indicate that imperfect verification can support effective RLVR in the tested settings, while aggregate error rates alone do not characterize the learning signal.
Andreas Lindhardt Plesner, F. Guzmán, Anish Athalye· arXiv.org· 10 citations· ⚡1
This paper compares two low-cost choices retrospectively -- a cost-reducing choice and a balanced choice -- with estimated grading cost reductions and average post-training score gaps of 1-3 points from the best evaluated training verifier, and establishes that verifier choices are interchangeable.
Andreas Lindhardt Plesner, Curtis G. Northcutt, F. Guzmán et al.· 0 citations
Artificial intelligence offers an unprecedented opportunity to augment human capabilities, yet progress at the frontier has focused primarily on advancing model capabilities. We introduce StudentBench, a suite of AI teaching evaluations and a public platform that enables large-scale data collection with over 175,000 st...
Curtis G. Northcutt, Inaara Hasmani, Kevin Feng et al.· 0 citations
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