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Let LRMs Break Free from Overthinking via Self-Braking Tuning

arXiv — cs.CL•Friday, October 31, 2025 at 4:00:00 AM
PositiveArtificial Intelligence
Recent advancements in large reasoning models (LRMs) like OpenAI's o1 and DeepSeek-R1 have shown remarkable improvements in their reasoning abilities, allowing them to tackle complex tasks more effectively. However, this progress has also led to increased redundant reasoning, which can slow down performance and create unnecessary computational demands. The introduction of self-braking tuning aims to address these challenges by streamlining the reasoning process, making it more efficient and reducing the burden of overthinking. This innovation is crucial as it not only enhances the models' capabilities but also makes them more practical for real-world applications.
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