AAAI 2026technical0 citations
Efficient Reasoning for Large Reasoning Language Models via Certainty-Guided Reflection Suppression
Jiameng Huang, Baijiong Lin, Guhao Feng, Jierun Chen, Di He, Lu Hou
Abstract
Recent Large Reasoning Language Models (LRLMs) employ long chain-of-thought reasoning with complex reflection behaviors, typically signaled by specific trigger words (e.g., "Wait" and "Alternatively") to enhance performance. However, these reflection behaviors can lead to the overthinking problem where the generation of redundant reasoning steps that unnecessarily increase token usage, raise inference costs, and reduce practical utility. In this paper, we propose Certainty-Guided Reflection Suppression (CGRS), a novel method that mitigates overthinking in LRLMs while maintaining reasoning accuracy. CGRS operates by dynamically suppressing the model
BibTeX
@inproceedings{aaai2026_efficientreasoni,
title = {Efficient Reasoning for Large Reasoning Language Models via Certainty-Guided Reflection Suppression},
author = {Jiameng Huang and Baijiong Lin and Guhao Feng and Jierun Chen and Di He and Lu Hou},
booktitle = {AAAI 2026},
year = {2026}
}