且慢，我們無需“等待”！移除思考標記提升推理效率

摘要

近期，大型推理模型的進展已能實現複雜的逐步推理，但往往伴隨著顯著的過度思考，導致冗長且重複的輸出，從而影響效率。本研究探討了以“等待”和“嗯”等標記為信號的顯式自我反思是否為高級推理所必需。我們提出了NoWait，這是一種簡單而有效的方法，通過在推理過程中抑制這些標記來禁用顯式自我反思。在涵蓋文本、視覺及視頻推理任務的十個基準上的廣泛實驗表明，NoWait在五個R1系列模型中，將思維鏈軌跡長度縮短了高達27%-51%，且不損害模型效用。因此，NoWait為高效且保持效用的多模態推理提供了一種即插即用的解決方案。

English

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.

且慢，我們無需“等待”！移除思考標記提升推理效率

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

摘要

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