This AI Paper from China Proposes a Novel Training-Free Approach DEER that Allows Large Reasoning Language Models to Achieve Dynamic Early Exit in Reasoning

This AI Paper from China Proposes a Novel Training-Free Approach DEER that Allows Large Reasoning Language Models to Achieve Dynamic Early Exit in Reasoning

Recent progress in large reasoning language models (LRLMs), such as DeepSeek-R1 and GPT-O1, has greatly improved complex problem-solving abilities by extending the length of CoT generation during inference. These models benefit from test-time scaling laws, allowing richer and more diverse reasoning paths. However, generating overly long CoT sequences leads to computational inefficiency and increased latency, making the deployment of real-world s…