AI & ML Paradigm Challenge

If you force an AI to overthink a problem for too long, it'll eventually talk itself out of the right answer and choose something stupid.

April 6, 2026

Original Paper

FoE: Forest of Errors Makes the First Solution the Best in Large Reasoning Models

Kehan Jiang, Haonan Dong, Zhaolu Kang, Zhengzhou Zhu, Guojie Song

arXiv · 2604.02967

The Takeaway

It contradicts the popular 'test-time scaling' trend, showing that refining an initial hunch is often more reliable than generating many alternatives. This discovery could make reasoning models much faster and more accurate by trimming wasted effort.

From the abstract

Recent Large Reasoning Models (LRMs) like DeepSeek-R1 have demonstrated remarkable success in complex reasoning tasks, exhibiting human-like patterns in exploring multiple alternative solutions. Upon closer inspection, however, we uncover a surprising phenomenon: The First is The Best, where alternative solutions are not merely suboptimal but potentially detrimental. This observation challenges widely accepted test-time scaling laws, leading us to hypothesize that errors within the reasoning pat