Reward models holding back AI? DeepSeek's SPCT creates self-guiding critiques, promising more scalable intelligence for enterprise LLMs.

Machine learning (ML) is a subset of artificial intelligence (AI) that focuses on enabling computers to learn from data and ...

Huang and colleagues examined neural responses in mouse anterior cingulate cortex (ACC) during a discrimination-avoidance task. The authors present useful findings that ACC neurons encode primarily ...

New approach flips the script on enterprise AI adoption by using input data you already have for fine-tuning instead of needing labelled data.

With this transition information, the system can better estimate the states to assist the decision making." The new reinforcement learning framework Teng and his colleagues developed could soon open ...

Reinforcement learning (RL) has become central to advancing Large Language Models (LLMs), empowering them with improved reasoning capabilities necessary for complex tasks. However, the research ...

Control theory and reinforcement learning share similar objectives, but have differed in their assumptions and approaches. This spring school emphasizes connections across control theory, ...

Abstract: Multiagent formation obstacle avoidance is a crucial research topic in the field of multiagent cooperative control, and deep reinforcement learning has shown remarkable potential in this ...