2 papers
cs.AI2026
Accelerating Long-Tail Generation in Synchronous RLHF Training via Adaptive Tensor Parallelism
Long Zhao, Qinghe Wang, Jiaan Zhu +5
Reinforcement Learning from Human Feedback (RLHF) has become a key post-training paradigm for improving model quality. However, the synchronous three-stage RLHF pipeline is often b…
cs.DC2026
AuroraRL: Fast, Fault-Tolerant, and Cost-Efficient Reinforcement Learning over Decentralized Network
Chaoyi Ruan, Geng Luo, Xinyi Wan +12
LLM reinforcement learning (RL) requires frequent synchronization of large model parameters between the trainer and distributed rollout actors. High-throughput RL post-training the…