Iterative reasoning states help multimodal models refine their own answers

ReState trains one multimodal model to construct, preserve and correct reasoning through repeated updates to a shared state.

Chinese Tech
Chuang Yu · Xuefei Ma · Yuanhao Feng · Wuxiong Zeng · Bo Wang · Minghong Cai · +6 more

MMLab, CUHK · PolyU · Tencent · Peking University · CPII

Research Digest··2 min read
Yu and colleagues recast multimodal chain-of-thought reasoning as an iterative state-update process rather than a sequence of separately trained stages.

ReState combines two mechanisms.

Why this paper

From Tencent and 4 others

In one line

ReState reformulates multimodal reasoning as dynamic state transitions, unifying construction, correction, and preservation for improved chain-of-thought.

What we could check

  • ·No code link found
  • ·No weights link found
  • ·No dataset link found
  • ·No compute details found
  • ·No stated limitations found
  • ·No benchmark numbers found

Observed from the paper text and links we have. Absence here means we did not find it, not that it does not exist.

§

Research Digest

Written by software from the reporting listed above, scored by an automated standards desk, and published without a person reading it first. If something here is wrong, tell the editor and it will be put right.

How we workSubscribe