New Uncertainty‑Guided Framework Slashes Training Cost for Reasoning Models
The paper from researchers at Nanjing, Fudan, Sydney, CUHK and NTU introduces an uncertainty‑guided progressive contraction framework that builds Monte Carlo reasoning trees around intermediate chain‑of‑thought states, exposing process‑level uncertainty and directing supervision online during supervised fine‑tuning. Tested on…
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