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Wait, We Don't Need to "Wait"! Removing Thinking Tokens Improves Reasoning Efficiency

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Recent advances in large reasoning models have enabled complex, step-by-step reasoning but often introduce significant overthinking, resulting in verbose and redundant outputs that hinder efficiency. In this study, we examine whether explicit self-reflection, signaled by tokens such as "Wait" and "Hmm", is necessary for advanced reasoning. We propose NoWait, a simple yet effective approach that disables explicit self-reflection by suppressing these tokens during inference. Extensive experiments on ten benchmarks across textual, visual, and video reasoning tasks show that NoWait reduces chain-of-thought trajectory length by up to 27%-51% in five R1-style model series, without compromising model utility. NoWait thus offers a plug-and-play solution for efficient and utility-preserving multimodal reasoning.

Chenlong Wang, Yuanning Feng, Dongping Chen, Zhaoyang Chu, Ranjay Krishna, Tianyi Zhou• 2025

Related benchmarks

TaskDatasetResultRank
Mathematical ReasoningAIME 2024
Accuracy53.8
394
Mathematical ReasoningGSM8K
Accuracy96.7
166
Mathematical ReasoningMATH 500
Average Tokens5.06e+3
104
Mathematical ReasoningAMC 2023
Accuracy79.6
104
Math ReasoningAMC23
Pass@1 Accuracy95
99
Mathematical ReasoningAMC 23
Pass@1 Accuracy100
71
Science ReasoningARC-C
Accuracy96.2
65
Math ReasoningGSM8K
Pass@1 Accuracy96.3
61
Mathematical ReasoningMATH500
Accuracy88.7
57
Mathematical ReasoningAIME 2024
Accuracy70
54
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