1 citations · 1 across the 3 of their papers we have counts for
4 papers
RollVerify: Bridging Efficiency and Accuracy in Long-Tail Rollout Reinforcement Learning
Yongqiang Yao, Jinru Tan, Kaihuan Liang +5
Reinforcement learning is crucial for improving large language models' reasoning and generalization. It relies on massive rollouts whose lengths become increasingly long-tailed as…
RhinoVLA Technical Report
Huixi Technology, :, Chen Zhang +13
Vision-Language-Action (VLA) models have shown strong potential for robotic manipulation, but real-time deployment on edge hardware remains challenging. In this work, we identify V…
Hierarchical Balance Packing: Towards Efficient Supervised Fine-tuning for Long-Context LLM
Yongqiang Yao, Jingru Tan, Kaihuan Liang +7
Training Long-Context Large Language Models (LLMs) is challenging, as hybrid training with long-context and short-context data often leads to workload imbalances. Existing works ma…
OmniBal: Towards Fast Instruction-Tuning for Vision-Language Models via Omniverse Computation Balance
Yongqiang Yao, Jingru Tan, Feizhao Zhang +8
Vision-language instruction-tuning models have recently achieved significant performance improvements. In this work, we discover that large-scale 3D parallel training on those mode…