The research has focused on a range of AI domains, including image recognition, natural language processing, and reinforcement learning. IARPA has published much of the research in conjunction with ...

We investigate Reinforcement Learning (RL) on data without explicit labels for reasoning tasks in Large Language Models (LLMs). The core challenge of the problem is reward estimation during inference ...

To address this problem, we propose a deep reinforcement learning method based on the Actor-Critic algorithm to quickly calculate the approximate optimal solution of FPDSP. Specifically, we propose a ...

This new NL2SQL model leverages reinforcement learning rather than traditional supervised learning. SQL-R1 uses feedback mechanisms during training to improve its performance. Instead of just learning ...

Welcome to the official repository for MT-R1-Zero, the first open-source adaptation of the R1-Zero Reinforcement Learning (RL) paradigm for Machine Translation (MT). MT-R1-Zero achieves highly ...

like Eriksen – who went into cardiac arrest during the 2020 Euros – is learning what it means to be an elite athlete with a heart problem. “I’m a football fan, I grew up in Copenhagen ...