CMU and Oxford paper: refining hidden state beats longer chain-of-thought for reasoning
rohanpaul_ai · x · 2026-09-18
A new Carnegie Mellon + Oxford paper shows models can 'think longer' by repeatedly refining their hidden state instead of generating longer chains of thought—test-time compute doesn't have to mean more tokens. Looped flows fix the instability of long recurrent loops by training each update on a small denoising task while keeping the hidden state useful for the next update, letting models keep improving the same internal representation at inference time and materially raising accuracy.
Related event: CMU and Oxford: Looping Hidden States Can Replace Long Chain-of-Thought(2 posts)→
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