Mind the Gap: Bridging Thought Leap for Improved Chain-of-Thought Tuning
Haolei Xu, Yuchen Yan, Yongliang Shen, Wenqi Zhang, Guiyang Hou, Shengpei Jiang, Kaitao Song, Weiming Lu, Jun Xiao, Yueting Zhuang
2025-05-23
Summary
This paper talks about a new method that helps AI models get better at solving math and logic problems by making sure they don't skip important steps when explaining their thinking.
What's the problem?
AI models often make mistakes on math or logic problems because they jump from one idea to the next without showing all the steps in between, which can lead to wrong answers or make it hard for people to follow their reasoning.
What's the solution?
The researchers created a system that can spot when an AI misses a step in its explanation and can also generate those missing steps, helping the model give more complete and accurate solutions.
Why it matters?
This matters because it makes AI much more reliable and understandable for things like homework help, tutoring, or any situation where clear step-by-step reasoning is important.
Abstract
A model for detecting and generating missing intermediate steps in mathematical Chain-of-Thought reasoning improves performance and generalization on mathematical and logical reasoning tasks.