Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...
MIT researchers unveil a new fine-tuning method that lets enterprises consolidate their "model zoos" into a single, continuously learning agent.
A new technique from Stanford, Nvidia, and Together AI lets models learn during inference rather than relying on static ...
From autonomous cars to video games, reinforcement learning (machine learning through interaction with environments) can have ...
Abstract: This article focuses on the issue of reinforcement learning (RL)-based adaptive optimal finite-time performance constraint control for nonlinear systems. By the aid of RL-based critic-actor ...
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.
ABSTRACT: Depression treatment often involves a complex and lengthy trial-and-error process, where clinicians sequentially prescribe medications to identify the most ...
Welcome to the Braze Fiscal First Quarter 2026 Earnings Conference Call. My name is Luke, and I'll be your operator for today's call. [Operator Instructions] I'll now turn the call over to Christopher ...
Our training pipeline is adapted from verl and rllm(DeepScaleR). The installation commands that we verified as viable are as follows: conda create -y -n rlvr_train ...
Recent advancements in LLMs such as OpenAI-o1, DeepSeek-R1, and Kimi-1.5 have significantly improved their performance on complex mathematical reasoning tasks. Reinforcement Learning with Verifiable ...
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