2 papers
cs.AI2025
OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework
Jian Hu, Xibin Wu, Wei Shen +12
Large Language Models (LLMs) fine-tuned via Reinforcement Learning from Human Feedback (RLHF) and Reinforcement Learning with Verifiable Rewards (RLVR) significantly improve the al…
cs.AI2025
QUASAR: Quantum Assembly Code Generation Using Tool-Augmented LLMs via Agentic RL
Cong Yu, Valter Uotila, Shilong Deng +5
Designing and optimizing task-specific quantum circuits are crucial to leverage the advantage of quantum computing. Recent large language model (LLM)-based quantum circuit generati…