ReThinker: Scientific Reasoning by Rethinking with Guided Reflection and Confidence Control
By: Zhentao Tang, Yuqi Cui, Shixiong Kai, Wenqian Zhao, Ke Ye, Xing Li, Anxin Tian, Zehua Pei, Hui-Ling Zhen, Shoubo Hu, Xiaoguang Li, Yunhe Wang, Mingxuan Yuan
Published: 2026-02-03
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Abstract
Expert-level scientific reasoning remains challenging for large language models, particularly on benchmarks such as Humanity's Last Exam (HLE), where rigid tool pipelines, brittle multi-agent coordination, and inefficient test-time scaling often limit performance. We introduce ReThinker, a confidence-aware agentic framework that enhances LLM scientific reasoning through guided reflection and adaptive confidence control. This enables models to identify and correct errors, leading to more reliable and accurate scientific inquiry.