The Problem with “Thinking Longer” Large language models have made impressive strides in mathematical reasoning by extending their Chain-of-Thought (CoT) processes—essentially “thinking longer” through more detailed reasoning steps. However, this approach has fundamental limitations. When models encounter subtle errors in their reasoning chains, they often compound these mistakes rather than detecting and correcting them. Internal […] The post Microsoft AI Introduces rStar2-Agent: A 14B Math Reasoning Model Trained with Agentic Reinforcement Learning to Achieve Frontier-Level Performance appeared first on MarkTechPost.
Microsoft AI Introduces rStar2-Agent: A 14B Math Reasoning Model Trained with Agentic Reinforcement Learning to Achieve Frontier-Level Performance
The Problem with “Thinking Longer” Large language models have made impressive strides in mathematical reasoning by extending their Chain-of-Thought (CoT) processes—essentially “thinking longer” through more detailed reasoning steps. However, this approach has fundamental limitations. When models encounter subtle errors in their reasoning chains, they often compound these mistakes rather than detecting and correcting them. Internal […] The post Microsoft AI Introduces rStar2-Agent: A 14B Math Reasoning Model Trained with Agentic Reinforcement Learning to Achieve Frontier-Level Performance appeared first on MarkTechPost.