Wait, We Don't Need to "Wait"! Removing Thinking Tokens Improves Reasoning Efficiency
By: Chenlong Wang , Yuanning Feng , Dongping Chen and more
Potential Business Impact:
Makes smart computer answers shorter and faster.
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.
Similar Papers
Reasoning Models Can Be Effective Without Thinking
Artificial Intelligence
Computers solve problems faster without thinking.
Internal states before wait modulate reasoning patterns
Artificial Intelligence
Helps computers think better by watching how they pause.
Dynamic Early Exit in Reasoning Models
Computation and Language
Computers solve problems faster and better.