Qinghao Hu

According to our database, Qinghao Hu authored at least 32 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Hide to Guide: Learning via Semantic Masking.

Ruitao Liu, Qinghao Hu, Alex Hu, Yecheng Wu, Shang Yang, Luke J. Huang, Zhuoyang Zhang, Han Cai, Song Han

CoRR, May, 2026

Stable Asynchrony: Variance-Controlled Off-Policy RL for LLMs.

Luke J. Huang, Zhuoyang Zhang, Qinghao Hu, Shang Yang, Song Han

CoRR, February, 2026

ForeAct: Steering Your VLA with Efficient Visual Foresight Planning.

Zhuoyang Zhang, Shang Yang, Qinghao Hu, Luke J. Huang, James Hou, Yufei Sun, Yao Lu, Song Han

CoRR, February, 2026

Zeppelin: Balancing Variable-length Workloads in Data Parallel Large Model Training.

Chang Chen, Tiancheng Chen, Jiangfei Duan, Qianchao Zhu, Zerui Wang, Qinghao Hu, Peng Sun, Xiuhong Li, Chao Yang, Torsten Hoefler

Proceedings of the 21st European Conference on Computer Systems, 2026

Taming the Long-Tail: Efficient Reasoning RL Training with Adaptive Drafter.

Qinghao Hu, Shang Yang, Junxian Guo, Xiaozhe Yao, Yujun Lin, Yuxian Gu, Han Cai, Chuang Gan, Ana Klimovic, Song Han

Proceedings of the 31st ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2026

2025

Taming the Long-Tail: Efficient Reasoning RL Training with Adaptive Drafter.

Qinghao Hu, Shang Yang, Junxian Guo, Xiaozhe Yao, Yujun Lin, Yuxian Gu, Han Cai, Chuang Gan, Ana Klimovic, Song Han

CoRR, November, 2025

Semantic-Aware Scheduling for GPU Clusters with Large Language Models.

Zerui Wang, Qinghao Hu, Ana Klimovic, Tianwei Zhang, Yonggang Wen, Peng Sun, Dahua Lin

CoRR, October, 2025

RL in the Wild: Characterizing RLVR Training in LLM Deployment.

Jiecheng Zhou, Qinghao Hu, Yuyang Jin, Zerui Wang, Peng Sun, Yuzhe Gu, Wenwei Zhang, Mingshu Zhai, Xingcheng Zhang, Weiming Zhang

CoRR, September, 2025

Jet-Nemotron: Efficient Language Model with Post Neural Architecture Search.

Yuxian Gu, Qinghao Hu, Shang Yang, Haocheng Xi, Junyu Chen, Song Han, Han Cai

CoRR, August, 2025

Sailor: Automating Distributed Training over Dynamic, Heterogeneous, and Geo-distributed Clusters.

Foteini Strati, Zhendong Zhang, George Manos, Ixeia Sánchez Périz, Qinghao Hu, Tiancheng Chen, Berk Buzcu, Song Han, Pamela Delgado, Ana Klimovic

Dataset, August, 2025

Sailor: Automating Distributed Training over Dynamic, Heterogeneous, and Geo-distributed Clusters.

Foteini Strati, Zhendong Zhang, George Manos, Ixeia Sánchez Périz, Qinghao Hu, Tiancheng Chen, Berk Buzcu, Song Han, Pamela Delgado, Ana Klimovic

Proceedings of the ACM SIGOPS 31st Symposium on Operating Systems Principles, 2025

Scaling RL to Long Videos.

Yukang Chen, Wei Huang, Baifeng Shi, Qinghao Hu, Hanrong Ye, Ligeng Zhu, Zhijian Liu, Pavlo Molchanov, Jan Kautz, Xiaojuan Qi, Sifei Liu, Hongxu Yin, Yao Lu, Song Han

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

LServe: Efficient Long-sequence LLM Serving with Unified Sparse Attention.

Shang Yang, Junxian Guo, Haotian Tang, Qinghao Hu, Guangxuan Xiao, Jiaming Tang, Yujun Lin, Zhijian Liu, Yao Lu, Song Han

Proceedings of the Eighth Conference on Machine Learning and Systems, 2025

LongVILA: Scaling Long-Context Visual Language Models for Long Videos.

Yukang Chen, Fuzhao Xue, Dacheng Li, Qinghao Hu, Ligeng Zhu, Xiuyu Li, Yunhao Fang, Haotian Tang, Shang Yang, Zhijian Liu, Yihui He, Hongxu Yin, Pavlo Molchanov, Jan Kautz, Linxi Fan, Yuke Zhu, Yao Lu, Song Han

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

DeltaZip: Efficient Serving of Multiple Full-Model-Tuned LLMs.

Xiaozhe Yao, Qinghao Hu, Ana Klimovic

Proceedings of the Twentieth European Conference on Computer Systems, 2025

2024

Deep Learning Workload Scheduling in GPU Datacenters: A Survey.

Zhisheng Ye, Wei Gao, Qinghao Hu, Peng Sun, Xiaolin Wang, Yingwei Luo, Tianwei Zhang, Yonggang Wen

ACM Comput. Surv., June, 2024

LongVILA: Scaling Long-Context Visual Language Models for Long Videos.

Fuzhao Xue, Yukang Chen, Dacheng Li, Qinghao Hu, Ligeng Zhu, Xiuyu Li, Yunhao Fang, Haotian Tang, Shang Yang, Zhijian Liu, Ethan He, Hongxu Yin, Pavlo Molchanov, Jan Kautz, Linxi Fan, Yuke Zhu, Yao Lu, Song Han

CoRR, 2024

Efficient Training of Large Language Models on Distributed Infrastructures: A Survey.

Jiangfei Duan, Shuo Zhang, Zerui Wang, Lijuan Jiang, Wenwen Qu, Qinghao Hu, Guoteng Wang, Qizhen Weng, Hang Yan, Xingcheng Zhang, Xipeng Qiu, Dahua Lin, Yonggang Wen, Xin Jin, Tianwei Zhang, Peng Sun

CoRR, 2024

LoongTrain: Efficient Training of Long-Sequence LLMs with Head-Context Parallelism.

Diandian Gu, Peng Sun, Qinghao Hu, Ting Huang, Xun Chen, Yingtong Xiong, Guoteng Wang, Qiaoling Chen, Shangchun Zhao, Jiarui Fang, Yonggang Wen, Tianwei Zhang, Xin Jin, Xuanzhe Liu

CoRR, 2024

InternEvo: Efficient Long-sequence Large Language Model Training via Hybrid Parallelism and Redundant Sharding.

Qiaoling Chen, Diandian Gu, Guoteng Wang, Xun Chen, Yingtong Xiong, Ting Huang, Qinghao Hu, Xin Jin, Yonggang Wen, Tianwei Zhang, Peng Sun

CoRR, 2024

FedDSE: Distribution-aware Sub-model Extraction for Federated Learning over Resource-constrained Devices.

Haozhao Wang, Yabo Jia, Meng Zhang, Qinghao Hu, Hao Ren, Peng Sun, Yonggang Wen, Tianwei Zhang

Proceedings of the ACM on Web Conference 2024, 2024

TorchGT: A Holistic System for Large-Scale Graph Transformer Training.

Meng Zhang, Jie Sun, Qinghao Hu, Peng Sun, Zeke Wang, Yonggang Wen, Tianwei Zhang

Proceedings of the International Conference for High Performance Computing, 2024

Characterization of Large Language Model Development in the Datacenter.

Qinghao Hu, Zhisheng Ye, Zerui Wang, Guoteng Wang, Meng Zhang, Qiaoling Chen, Peng Sun, Dahua Lin, Xiaolin Wang, Yingwei Luo, Yonggang Wen, Tianwei Zhang

Proceedings of the 21st USENIX Symposium on Networked Systems Design and Implementation, 2024

Lins: Reducing Communication Overhead of ZeRO for Efficient LLM Training.

Qiaoling Chen, Qinghao Hu, Guoteng Wang, Yingtong Xiong, Ting Huang, Xun Chen, Yang Gao, Hang Yan, Yonggang Wen, Tianwei Zhang, Peng Sun

Proceedings of the 32nd IEEE/ACM International Symposium on Quality of Service, 2024

Sylvie: 3D-Adaptive and Universal System for Large-Scale Graph Neural Network Training.

Meng Zhang, Qinghao Hu, Cheng Wan, Haozhao Wang, Peng Sun, Yonggang Wen, Tianwei Zhang

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

2023

AMSP: Super-Scaling LLM Training via Advanced Model States Partitioning.

Qiaoling Chen, Qinghao Hu, Zhisheng Ye, Guoteng Wang, Peng Sun, Yonggang Wen, Tianwei Zhang

CoRR, 2023

Boosting Distributed Full-graph GNN Training with Asynchronous One-bit Communication.

Meng Zhang, Qinghao Hu, Peng Sun, Yonggang Wen, Tianwei Zhang

CoRR, 2023

Hydro: Surrogate-Based Hyperparameter Tuning Service in Datacenters.

Qinghao Hu, Zhisheng Ye, Meng Zhang, Qiaoling Chen, Peng Sun, Yonggang Wen, Tianwei Zhang

Proceedings of the 17th USENIX Symposium on Operating Systems Design and Implementation, 2023

Lucid: A Non-intrusive, Scalable and Interpretable Scheduler for Deep Learning Training Jobs.

Qinghao Hu, Meng Zhang, Peng Sun, Yonggang Wen, Tianwei Zhang

Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023

2022

Deep Learning Workload Scheduling in GPU Datacenters: Taxonomy, Challenges and Vision.

Wei Gao, Qinghao Hu, Zhisheng Ye, Peng Sun, Xiaolin Wang, Yingwei Luo, Tianwei Zhang, Yonggang Wen

CoRR, 2022

Primo: Practical Learning-Augmented Systems with Interpretable Models.

Qinghao Hu, Harsha Nori, Peng Sun, Yonggang Wen, Tianwei Zhang

Proceedings of the 2022 USENIX Annual Technical Conference, 2022

2021

Characterization and prediction of deep learning workloads in large-scale GPU datacenters.

Qinghao Hu, Peng Sun, Shengen Yan, Yonggang Wen, Tianwei Zhang

Proceedings of the International Conference for High Performance Computing, 2021