Publications

2024

1. ExpertFlow: Optimized Expert Activation and Token Allocation for Efficient Mixture-of-Experts Inference

   Xin He , Shunkang Zhang , Yuxin Wang , and 7 more authors

   2024

   Bib PDF

   

   @article{he2024expertflowoptimizedexpertactivation,
     title = {ExpertFlow: Optimized Expert Activation and Token Allocation for Efficient Mixture-of-Experts Inference},
     author = {He, Xin and Zhang, Shunkang and Wang, Yuxin and Yin, Haiyan and Zeng, Zihao and Shi, Shaohuai and Tang, Zhenheng and Chu, Xiaowen and Tsang, Ivor and Soon, Ong Yew},
     year = {2024},
     eprint = {2410.17954},
     archiveprefix = {arXiv},
     primaryclass = {cs.AI},
     url = {https://arxiv.org/abs/2410.17954},
     google_scholar_id = {LkGwnXOMwfcC}
   }

2. FusionLLM: A Decentralized LLM Training System on Geo-distributed GPUs with Adaptive Compression

   Zhenheng Tang , Xueze Kang , Yiming Yin , and 8 more authors

   arXiv preprint arXiv:2410.12707, 2024
3. BurstGPT: A Real-world Workload Dataset to Optimize LLM Serving Systems

   Yuxin Wang , Yuhan Chen , Zeyu Li , and 8 more authors

   2024

   Code
4. Fault-Tolerant Hybrid-Parallel Training at Scale with Reliable and Efficient In-memory Checkpointing

   Yuxin Wang , Xueze Kang , Shaohuai Shi , and 8 more authors

   2024

2023

1. MedAI

   MedPipe: End-to-End Joint Search of Data Augmentation Policy and Neural Architecture for 3D Medical Image Classification

   Xin He , and Xiaowen Chu

   IEEE MedAI, 2023

   Bib PDF Code

   

   @article{medpipe,
     title = {MedPipe: End-to-End Joint Search of Data Augmentation Policy and Neural Architecture for 3D Medical Image Classification},
     author = {He, Xin and Chu, Xiaowen},
     journal = {IEEE MedAI},
     year = {2023},
     publisher = {IEEE MedAI},
     google_scholar_id = {u-x6o8ySG0sC}
   }

2. AAAI

   NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension

   Xin He , Jiangchao Yao , Yuxin Wang , and 5 more authors

   AAAI, 2023

   Bib PDF Code

   

   @article{NASLID,
     title = {NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension},
     author = {He, Xin and Yao, Jiangchao and Wang, Yuxin and Tang, Zhenheng and Ka Chun, Cheung and Simon, See and Han, Bo and Chu, Xiaowen},
     booktitle = {AAAI},
     year = {2023},
     journal = {AAAI},
     corr = {true},
     zhihu = {https://zhuanlan.zhihu.com/p/591027254},
     special = {CCF-A},
     gamma = {https://gamma.app/public/0t1h94j75bccc0q},
     dimensions = {true},
     google_scholar_id = {Tyk-4Ss8FVUC}
   }

3. IJCAI-LLM

   FusionAI: Decentralized Training and Deploying LLMs with Massive Consumer-Level GPUs

   Zhenheng Tang , Yuxin Wang , Xin He , and 8 more authors

   In IJCAI-LLM Workshop , 2023

   Bib PDF

   

   @inproceedings{tang2023fusionai,
     title = {FusionAI: Decentralized Training and Deploying LLMs with Massive Consumer-Level GPUs},
     author = {Tang, Zhenheng and Wang, Yuxin and He, Xin and Zhang, Longteng and Pan, Xinglin and Wang, Qiang and Zeng, Rongfei and Zhao, Kaiyong and Shi, Shaohuai and He, Bingsheng and Chu, Xiaowen},
     year = {2023},
     corr = {true},
     journal = {IJCAI-LLM Workshop},
     booktitle = {IJCAI-LLM Workshop},
     google_scholar_id = {W7OEmFMy1HYC},
   }

2022

1. MICCAI

   Evolutionary Multi-objective Architecture Search Framework: Application to COVID-19 3D CT Classification

   Xin He , Guohao Ying , Jiyong Zhang , and 1 more author

   In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) , 2022

   Bib PDF Code

   

   @inproceedings{emars,
     title = {Evolutionary Multi-objective Architecture Search Framework: Application to COVID-19 3D CT Classification},
     author = {He, Xin and Ying, Guohao and Zhang, Jiyong and Chu, Xiaowen},
     booktitle = {International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)},
     pages = {560--570},
     year = {2022},
     corr = {true},
     special = {CCF-B},
     zhihu = {https://zhuanlan.zhihu.com/p/542168478},
     dimensions = {true},
     google_scholar_id = {UeHWp8X0CEIC},
     special_old = {top premier international conferences for medical image analysis}
   }

2. ECCV

   EAGAN: Efficient Two-stage Evolutionary Architecture Search for GANs

   Guohao Ying , Xin He , Bin Gao , and 2 more authors

   In ECCV , 2022

   Bib PDF Code

   

   @inproceedings{ying2021eagan,
     title = {EAGAN: Efficient Two-stage Evolutionary Architecture Search for GANs},
     author = {Ying, Guohao and He, Xin and Gao, Bin and Han, Bo and Chu, Xiaowen},
     booktitle = {ECCV},
     corr = {true},
     zhihu = {https://zhuanlan.zhihu.com/p/542169585},
     special = {Co-first author; CCF-B},
     dimensions = {true},
     google_scholar_id = {qjMakFHDy7sC},
     year = {2022}
   }

3. ICML

   Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning

   Zhenheng Tang , Yonggang Zhang , Shaohuai Shi , and 3 more authors

   In , 2022

   Bib PDF Code

   

   @inproceedings{tang2022virtual,
     title = {Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning},
     author = {Tang, Zhenheng and Zhang, Yonggang and Shi, Shaohuai and He, Xin and Han, Bo and Chu, Xiaowen},
     journal = {ICML},
     special = {CCF-A},
     corr = {true},
     google_scholar_id = {9yKSN-GCB0IC},
     year = {2022}
   }

2021

1. KBS

   AutoML: A survey of the state-of-the-art

   Xin He , Kaiyong Zhao , and Xiaowen Chu

   Knowledge-Based Systems, 2021

   Bib PDF Website

   

   @article{he2021automl,
     title = {AutoML: A survey of the state-of-the-art},
     author = {He, Xin and Zhao, Kaiyong and Chu, Xiaowen},
     journal = {Knowledge-Based Systems},
     volume = {212},
     pages = {106622},
     year = {2021},
     publisher = {Elsevier},
     special = {CCF-C, 1300+ citations by Oct 2023.},
     zhihu = {https://zhuanlan.zhihu.com/p/158162306},
     corr = {true},
     dimensions = {true},
     google_scholar_id = {zYLM7Y9cAGgC}
   }

2. AAAI

   Automated Model Design and Benchmarking of 3D Deep Learning Models for COVID-19 Detection with Chest CT Scans

   Xin He , Shihao Wang , Xiaowen Chu , and 6 more authors

   In AAAI , 2021

   Bib PDF

   

   @inproceedings{He2021AutomatedMD,
     title = {Automated Model Design and Benchmarking of 3D Deep Learning Models for COVID-19 Detection with Chest CT Scans},
     author = {He, Xin and Wang, Shihao and Chu, Xiaowen and Shi, Shaohuai and Tang, J. and Liu, Xin and Yan, Chenggang Clarence and Zhang, Jiyong and Ding, Guiguang},
     booktitle = {AAAI},
     year = {2021},
     corr = {true},
     special = {CCF-A},
     dimensions = {true},
     google_scholar_id = {2osOgNQ5qMEC},
   }

2020

1. CCGRID

   Benchmarking the performance and energy efficiency of AI accelerators for AI training

   Yuxin Wang , Qiang Wang , Shaohuai Shi , and 4 more authors

   In 2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID) Workshop , 2020

   Bib

   

   @inproceedings{wang2020benchmarking,
     title = {Benchmarking the performance and energy efficiency of AI accelerators for AI training},
     author = {Wang, Yuxin and Wang, Qiang and Shi, Shaohuai and He, Xin and Tang, Zhenheng and Zhao, Kaiyong and Chu, Xiaowen},
     booktitle = {2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID) Workshop},
     pages = {744--751},
     year = {2020},
     corr = {true},
     organization = {IEEE},
     google_scholar_id = {d1gkVwhDpl0C}
   }

2. Benchmarking deep learning models and automated model design for COVID-19 detection with chest CT scans

   Xin He , Shihao Wang , Shaohuai Shi , and 6 more authors

   MedRxiv, 2020

   Bib PDF

   

   @article{he2020benchmarking,
     title = {Benchmarking deep learning models and automated model design for COVID-19 detection with chest CT scans},
     author = {He, Xin and Wang, Shihao and Shi, Shaohuai and Chu, Xiaowen and Tang, Jiangping and Liu, Xin and Yan, Chenggang and Zhang, Jiyong and Ding, Guiguang},
     journal = {MedRxiv},
     year = {2020},
     corr = {true},
     publisher = {Cold Spring Harbor Laboratory Press},
     zhihu = {https://zhuanlan.zhihu.com/p/147361922},
     google_scholar_id = {IjCSPb-OGe4C},
   }

2019

1. Big Data

   Computer-Aided Clinical Skin Disease Diagnosis Using CNN and Object Detection Models

   Xin He , Shihao Wang , Shaohuai Shi , and 8 more authors

   In 2019 IEEE International Conference on Big Data (Big Data) Workshop , 2019

   Bib PDF

   

   @inproceedings{he2019computer,
     title = {Computer-Aided Clinical Skin Disease Diagnosis Using CNN and Object Detection Models},
     author = {He, Xin and Wang, Shihao and Shi, Shaohuai and Tang, Zhenheng and Wang, Yuxin and Zhao, Zhihao and Dai, Jing and Ni, Ronghao and Zhang, Xiaofeng and Liu, Xiaoming and others},
     booktitle = {2019 IEEE International Conference on Big Data (Big Data) Workshop},
     pages = {4839--4844},
     year = {2019},
     corr = {true},
     organization = {IEEE},
     url = {https://ieeexplore.ieee.org/document/9006528},
     google_scholar_id = {eQOLeE2rZwMC},
   }