Waypoint-OPD released
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Waypoint-OPD released — rather than taking the teacher model's change in probabilities before and after reinforcement learning as it stands, it compares them with a midpoint of the same training run and, where the direction of change before and after disagrees, damps that signal as it transfers it to the student model
Why it matters
It starts from the point that looking only at the endpoints lets preference changes from early and late training cancel each other out and hide the parts where the teacher changed consistently. The authors reported that with a Qwen3-4B teacher and three Qwen3-family students, in all six settings compared across the two domains of math and code, it had the highest domain average among the methods compared
Source — Primary sources first; secondary reports are labelled “Press”
Paperarxiv.orghttps://arxiv.org/abs/2610.21601Added in Week 43, 2026 · See that week
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