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2020 – today
- 2025
[c19]Peijie Dong, Lujun Li, Zhenheng Tang, Xiang Liu, Zimian Wei, Qiang Wang, Xiaowen Chu:
ParZC: Parametric Zero-Cost Proxies for Efficient NAS. AAAI 2025: 16327-16335- [c18]Xinglin Pan
, Wenxiang Lin, Lin Zhang, Shaohuai Shi, Zhenheng Tang, Rui Wang, Bo Li, Xiaowen Chu:
FSMoE: A Flexible and Scalable Training System for Sparse Mixture-of-Experts Models. ASPLOS (1) 2025: 524-539 - [i34]Qian Wang, Jiaying Wu, Zhenheng Tang, Bingqiao Luo, Nuo Chen, Wei Chen, Bingsheng He:
What Limits LLM-based Human Simulation: LLMs or Our Design? CoRR abs/2501.08579 (2025) - [i33]Xinglin Pan, Wenxiang Lin, Lin Zhang, Shaohuai Shi, Zhenheng Tang, Rui Wang, Bo Li, Xiaowen Chu:
FSMoE: A Flexible and Scalable Training System for Sparse Mixture-of-Experts Models. CoRR abs/2501.10714 (2025) - [i32]Xiang Liu, Zhenheng Tang, Peijie Dong, Zeyu Li, Bo Li, Xuming Hu, Xiaowen Chu:
ChunkKV: Semantic-Preserving KV Cache Compression for Efficient Long-Context LLM Inference. CoRR abs/2502.00299 (2025) - [i31]Xiang Liu, Zhenheng Tang, Hong Chen, Peijie Dong, Zeyu Li, Xiuze Zhou, Bo Li, Xuming Hu, Xiaowen Chu:
Can LLMs Maintain Fundamental Abilities under KV Cache Compression? CoRR abs/2502.01941 (2025) - [i30]Kunfeng Lai, Zhenheng Tang, Xinglin Pan, Peijie Dong, Xiang Liu, Haolan Chen, Li Shen, Bo Li, Xiaowen Chu:
Mediator: Memory-efficient LLM Merging with Less Parameter Conflicts and Uncertainty Based Routing. CoRR abs/2502.04411 (2025) - [i29]Xiang Liu, Zhenheng Tang, Xia Li, Yijun Song, Sijie Ji, Zemin Liu, Bo Han, Linshan Jiang, Jialin Li:
One-shot Federated Learning Methods: A Practical Guide. CoRR abs/2502.09104 (2025) - [i28]Zhenheng Tang, Zichen Tang, Junlin Huang, Xinglin Pan, Rudan Yan, Yuxin Wang, Amelie Chi Zhou, Shaohuai Shi, Xiaowen Chu, Bo Li:
DreamDDP: Accelerating Data Parallel Distributed LLM Training with Layer-wise Scheduled Partial Synchronization. CoRR abs/2502.11058 (2025) - [i27]Zhenheng Tang, Xiang Liu, Qian Wang, Peijie Dong, Bingsheng He, Xiaowen Chu, Bo Li:
The Lottery LLM Hypothesis, Rethinking What Abilities Should LLM Compression Preserve? CoRR abs/2502.17535 (2025) - [i26]Qian Wang, Zhenheng Tang, Bingsheng He:
From ChatGPT to DeepSeek: Can LLMs Simulate Humanity? CoRR abs/2502.18210 (2025) - 2024
- [c17]Yujin Tang, Peijie Dong, Zhenheng Tang, Xiaowen Chu, Junwei Liang:
VMRNN: Integrating Vision Mamba and LSTM for Efficient and Accurate Spatiotemporal Forecasting. CVPR Workshops 2024: 5663-5673 - [c16]Peijie Dong, Lujun Li, Xiang Liu, Zhenheng Tang, Xuebo Liu, Qiang Wang, Xiaowen Chu:
LPZero: Language Model Zero-cost Proxy Search from Zero. EMNLP (Findings) 2024: 8592-8614 - [c15]Zhenheng Tang, Yonggang Zhang, Shaohuai Shi, Xinmei Tian, Tongliang Liu, Bo Han, Xiaowen Chu:
FedImpro: Measuring and Improving Client Update in Federated Learning. ICLR 2024 - [c14]Peijie Dong, Lujun Li, Zhenheng Tang, Xiang Liu, Xinglin Pan, Qiang Wang, Xiaowen Chu:
Pruner-Zero: Evolving Symbolic Pruning Metric From Scratch for Large Language Models. ICML 2024 - [c13]Zichen Tang, Junlin Huang, Rudan Yan, Yuxin Wang, Zhenheng Tang, Shaohuai Shi, Amelie Chi Zhou, Xiaowen Chu:
Bandwidth-Aware and Overlap-Weighted Compression for Communication-Efficient Federated Learning. ICPP 2024: 866-875 - [c12]Lujun Li, Peijie Dong, Zhenheng Tang, Xiang Liu, Qiang Wang, Wenhan Luo, Wei Xue, Qifeng Liu, Xiaowen Chu, Yike Guo:
Discovering Sparsity Allocation for Layer-wise Pruning of Large Language Models. NeurIPS 2024 - [c11]Qi Li, Xiang Liu, Zhenheng Tang, Peijie Dong, Zeyu Li, Xinglin Pan, Xiaowen Chu:
Should We Really Edit Language Models? On the Evaluation of Edited Language Models. NeurIPS 2024 - [c10]Zhenheng Tang, Yonggang Zhang, Peijie Dong, Yiu-ming Cheung, Amelie Chi Zhou, Bo Han, Xiaowen Chu:
FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion. NeurIPS 2024 - [i25]Yuxin Wang, Yuhan Chen, Zeyu Li, Zhenheng Tang, Rui Guo, Xin Wang, Qiang Wang, Amelie Chi Zhou, Xiaowen Chu:
Towards Efficient and Reliable LLM Serving: A Real-World Workload Study. CoRR abs/2401.17644 (2024) - [i24]Zhenheng Tang, Yonggang Zhang, Shaohuai Shi, Xinmei Tian, Tongliang Liu, Bo Han, Xiaowen Chu:
FedImpro: Measuring and Improving Client Update in Federated Learning. CoRR abs/2402.07011 (2024) - [i23]Yujin Tang, Peijie Dong, Zhenheng Tang, Xiaowen Chu, Junwei Liang:
VMRNN: Integrating Vision Mamba and LSTM for Efficient and Accurate Spatiotemporal Forecasting. CoRR abs/2403.16536 (2024) - [i22]Peijie Dong, Lujun Li, Zhenheng Tang, Xiang Liu, Xinglin Pan, Qiang Wang, Xiaowen Chu:
Pruner-Zero: Evolving Symbolic Pruning Metric from scratch for Large Language Models. CoRR abs/2406.02924 (2024) - [i21]Peijie Dong, Lujun Li, Dayou Du, Yuhan Chen, Zhenheng Tang, Qiang Wang, Wei Xue, Wenhan Luo, Qifeng Liu, Yike Guo, Xiaowen Chu:
STBLLM: Breaking the 1-Bit Barrier with Structured Binary LLMs. CoRR abs/2408.01803 (2024) - [i20]Zichen Tang, Junlin Huang, Rudan Yan, Yuxin Wang, Zhenheng Tang, Shaohuai Shi, Amelie Chi Zhou, Xiaowen Chu:
Bandwidth-Aware and Overlap-Weighted Compression for Communication-Efficient Federated Learning. CoRR abs/2408.14736 (2024) - [i19]Peijie Dong, Lujun Li, Xiang Liu, Zhenheng Tang, Xuebo Liu, Qiang Wang, Xiaowen Chu:
LPZero: Language Model Zero-cost Proxy Search from Zero. CoRR abs/2410.04808 (2024) - [i18]Qian Wang, Yuchen Gao, Zhenheng Tang, Bingqiao Luo, Bingsheng He:
Enhancing LLM Trading Performance with Fact-Subjectivity Aware Reasoning. CoRR abs/2410.12464 (2024) - [i17]Zhenheng Tang, Xueze Kang, Yiming Yin, Xinglin Pan, Yuxin Wang, Xin He, Qiang Wang, Rongfei Zeng, Kaiyong Zhao, Shaohuai Shi, Amelie Chi Zhou, Bo Li, Bingsheng He, Xiaowen Chu:
FusionLLM: A Decentralized LLM Training System on Geo-distributed GPUs with Adaptive Compression. CoRR abs/2410.12707 (2024) - [i16]Xin He, Shunkang Zhang, Yuxin Wang, Haiyan Yin, Zihao Zeng, Shaohuai Shi, Zhenheng Tang, Xiaowen Chu, Ivor W. Tsang, Yew-Soon Ong:
ExpertFlow: Optimized Expert Activation and Token Allocation for Efficient Mixture-of-Experts Inference. CoRR abs/2410.17954 (2024) - [i15]Qi Li, Xiang Liu, Zhenheng Tang, Peijie Dong, Zeyu Li, Xinglin Pan, Xiaowen Chu:
Should We Really Edit Language Models? On the Evaluation of Edited Language Models. CoRR abs/2410.18785 (2024) - [i14]Zhenheng Tang, Yonggang Zhang, Peijie Dong, Yiu-ming Cheung, Amelie Chi Zhou, Bo Han, Xiaowen Chu:
FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion. CoRR abs/2410.20380 (2024) - 2023
- [j2]Zhenheng Tang, Shaohuai Shi, Bo Li, Xiaowen Chu:
GossipFL: A Decentralized Federated Learning Framework With Sparsified and Adaptive Communication. IEEE Trans. Parallel Distributed Syst. 34(3): 909-922 (2023) - [c9]Xin He, Jiangchao Yao, Yuxin Wang, Zhenheng Tang, Ka Chun Cheung, Simon See, Bo Han, Xiaowen Chu:
NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension. AAAI 2023: 7839-7847 - [i13]Zhenheng Tang, Xiaowen Chu, Ryan Yide Ran, Sunwoo Lee, Shaohuai Shi, Yonggang Zhang, Yuxin Wang, Alex Qiaozhong Liang, Salman Avestimehr, Chaoyang He:
FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training. CoRR abs/2303.01778 (2023) - [i12]Zhenheng Tang, Yuxin Wang, Xin He, Longteng Zhang, Xinglin Pan, Qiang Wang, Rongfei Zeng, Kaiyong Zhao, Shaohuai Shi, Bingsheng He, Xiaowen Chu:
FusionAI: Decentralized Training and Deploying LLMs with Massive Consumer-Level GPUs. CoRR abs/2309.01172 (2023) - [i11]Yuxin Wang, Shaohuai Shi, Xin He, Zhenheng Tang, Xinglin Pan, Yang Zheng, Xiaoyu Wu, Amelie Chi Zhou, Bingsheng He, Xiaowen Chu:
Reliable and Efficient In-Memory Fault Tolerance of Large Language Model Pretraining. CoRR abs/2310.12670 (2023) - 2022
- [c8]Zhenheng Tang, Yonggang Zhang, Shaohuai Shi, Xin He, Bo Han, Xiaowen Chu:
Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning. ICML 2022: 21111-21132 - [i10]Zhenheng Tang, Yonggang Zhang, Shaohuai Shi, Xin He, Bo Han, Xiaowen Chu:
Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning. CoRR abs/2206.02465 (2022) - [i9]Xin He, Jiangchao Yao, Yuxin Wang, Zhenheng Tang, Ka Chun Cheung, Simon See, Bo Han, Xiaowen Chu:
NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension. CoRR abs/2211.12759 (2022) - 2021
- [j1]Shaohuai Shi, Zhenheng Tang, Xiaowen Chu, Chengjian Liu, Wei Wang, Bo Li:
A Quantitative Survey of Communication Optimizations in Distributed Deep Learning. IEEE Netw. 35(3): 230-237 (2021) - [i8]Chaoyang He, Alay Dilipbhai Shah, Zhenheng Tang, Di Fan, Adarshan Naiynar Sivashunmugam, Keerti Bhogaraju, Mita Shimpi, Li Shen, Xiaowen Chu, Mahdi Soltanolkotabi, Salman Avestimehr:
FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks. CoRR abs/2111.11066 (2021) - 2020
- [c7]Yuxin Wang, Qiang Wang, Shaohuai Shi, Xin He, Zhenheng Tang, Kaiyong Zhao, Xiaowen Chu:
Benchmarking the Performance and Energy Efficiency of AI Accelerators for AI Training. CCGRID 2020: 744-751 - [c6]Shaohuai Shi, Zhenheng Tang, Qiang Wang, Kaiyong Zhao, Xiaowen Chu:
Layer-Wise Adaptive Gradient Sparsification for Distributed Deep Learning with Convergence Guarantees. ECAI 2020: 1467-1474 - [c5]Zhenheng Tang, Shaohuai Shi, Xiaowen Chu:
Communication-Efficient Decentralized Learning with Sparsification and Adaptive Peer Selection. ICDCS 2020: 1207-1208 - [i7]Zhenheng Tang, Shaohuai Shi, Xiaowen Chu:
Communication-Efficient Decentralized Learning with Sparsification and Adaptive Peer Selection. CoRR abs/2002.09692 (2020) - [i6]Zhenheng Tang, Shaohuai Shi, Xiaowen Chu, Wei Wang, Bo Li:
Communication-Efficient Distributed Deep Learning: A Comprehensive Survey. CoRR abs/2003.06307 (2020) - [i5]Shaohuai Shi, Zhenheng Tang, Xiaowen Chu, Chengjian Liu, Wei Wang, Bo Li:
Communication-Efficient Distributed Deep Learning: Survey, Evaluation, and Challenges. CoRR abs/2005.13247 (2020)
2010 – 2019
- 2019
- [c4]Xin He, Xiaoming Liu, Zhili Wu, Wu Yu, Xiaowen Chu, Shihao Wang, Shaohuai Shi, Zhenheng Tang, Yuxin Wang, Zhihao Zhao, Jing Dai, Ronghao Ni, Xiaofeng Zhang:
Computer-Aided Clinical Skin Disease Diagnosis Using CNN and Object Detection Models. IEEE BigData 2019: 4839-4844 - [c3]Zhenheng Tang, Yuxin Wang, Qiang Wang, Xiaowen Chu:
The Impact of GPU DVFS on the Energy and Performance of Deep Learning: an Empirical Study. e-Energy 2019: 315-325 - [c2]Shaohuai Shi, Qiang Wang, Kaiyong Zhao, Zhenheng Tang, Yuxin Wang, Xiang Huang, Xiaowen Chu:
A Distributed Synchronous SGD Algorithm with Global Top-k Sparsification for Low Bandwidth Networks. ICDCS 2019: 2238-2247 - [c1]Shaohuai Shi, Kaiyong Zhao, Qiang Wang, Zhenheng Tang, Xiaowen Chu:
A Convergence Analysis of Distributed SGD with Communication-Efficient Gradient Sparsification. IJCAI 2019: 3411-3417 - [i4]Shaohuai Shi, Qiang Wang, Kaiyong Zhao, Zhenheng Tang, Yuxin Wang, Xiang Huang, Xiaowen Chu:
A Distributed Synchronous SGD Algorithm with Global Top-k Sparsification for Low Bandwidth Networks. CoRR abs/1901.04359 (2019) - [i3]Zhenheng Tang, Yuxin Wang, Qiang Wang, Xiaowen Chu:
The Impact of GPU DVFS on the Energy and Performance of Deep Learning: an Empirical Study. CoRR abs/1905.11012 (2019) - [i2]Xin He, Shihao Wang, Shaohuai Shi, Zhenheng Tang, Yuxin Wang, Zhihao Zhao, Jing Dai, Ronghao Ni, Xiaofeng Zhang, Xiaoming Liu, Zhili Wu, Wu Yu, Xiaowen Chu:
Computer-Aided Clinical Skin Disease Diagnosis Using CNN and Object Detection Models. CoRR abs/1911.08705 (2019) - [i1]Shaohuai Shi, Zhenheng Tang, Qiang Wang, Kaiyong Zhao, Xiaowen Chu:
Layer-wise Adaptive Gradient Sparsification for Distributed Deep Learning with Convergence Guarantees. CoRR abs/1911.08727 (2019)
Coauthor Index
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