verl is a flexible, efficient and production-ready RL training library for large language models (LLMs). verl is the open-source version of HybridFlow: A Flexible and Efficient RLHF Framework paper.
Researchers from Stony Brook University, in collaboration with Ecosuite and Ecogy Energy, have developed a self-supervised machine-learning algorithm designed to identify physical anomalies in solar ...
AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...
Abstract: Recent studies reveal that deep learning networks can reduce the radar cross section (RCS) of antenna arrays. However, the existing deep learning networks are all for a fixed frequency band.
Abstract: Achieving perfect Channel State Information at the Transmitter (CSIT) is often infeasible in Extremely Large-scale Antenna Array (ELAA) systems due to user mobility and feedback/processing ...