Computer-Aided Clinical Skin Disease Diagnosis Using CNN and Object Detection Models. - Xin He; Xiaoming Liu; Zhili Wu; Wu Yu; Xiaowen Chu 001; Shihao Wang; Shaohuai Shi; Zhenheng Tang; Yuxin Wang 003; Zhihao Zhao; Jing Dai; Ronghao Ni; et al. (IEEE BigData, 2019)

The Impact of GPU DVFS on the Energy and Performance of Deep Learning: an Empirical Study. - Zhenheng Tang; Yuxin Wang 003; Qiang Wang 022; Xiaowen Chu 001 (e-Energy, 2019)

A Distributed Synchronous SGD Algorithm with Global Top-k Sparsification for Low Bandwidth Networks. - Shaohuai Shi; Qiang Wang 022; Kaiyong Zhao; Zhenheng Tang; Yuxin Wang 003; Xiang Huang; Xiaowen Chu 001 (ICDCS, 2019)

A Convergence Analysis of Distributed SGD with Communication-Efficient Gradient Sparsification. - Shaohuai Shi; Kaiyong Zhao; Qiang Wang 022; Zhenheng Tang; Xiaowen Chu 001 (IJCAI, 2019)

Benchmarking the Performance and Energy Efficiency of AI Accelerators for AI Training. - Yuxin Wang 003; Qiang Wang 022; Shaohuai Shi; Xin He; Zhenheng Tang; Kaiyong Zhao; Xiaowen Chu 001 (CCGRID, 2020)

Layer-Wise Adaptive Gradient Sparsification for Distributed Deep Learning with Convergence Guarantees. - Shaohuai Shi; Zhenheng Tang; Qiang Wang 022; Kaiyong Zhao; Xiaowen Chu 001 (ECAI, 2020)

Communication-Efficient Decentralized Learning with Sparsification and Adaptive Peer Selection. - Zhenheng Tang; Shaohuai Shi; Xiaowen Chu 001 (ICDCS, 2020)

Communication-Efficient Distributed Deep Learning: A Comprehensive Survey. - Zhenheng Tang; Shaohuai Shi; Xiaowen Chu 001; Wei Wang 030; Bo Li 001 (CoRR, 2020)

Communication-Efficient Distributed Deep Learning: Survey, Evaluation, and Challenges. - Shaohuai Shi; Zhenheng Tang; Xiaowen Chu 001; Chengjian Liu; Wei Wang 030; Bo Li 001 (CoRR, 2020)

FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks. - Chaoyang He 001; Alay Dilipbhai Shah; Zhenheng Tang; Di Fan; Adarshan Naiynar Sivashunmugam; Keerti Bhogaraju; Mita Shimpi; Li Shen 005; Xiaowen Chu 001; Mahdi Soltanolkotabi; Salman Avestimehr (CoRR, 2021)

A Quantitative Survey of Communication Optimizations in Distributed Deep Learning. - Shaohuai Shi; Zhenheng Tang; Xiaowen Chu 001; Chengjian Liu; Wei Wang 030; Bo Li 001 (IEEE Netw., 2021)

Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning. - Zhenheng Tang; Yonggang Zhang 003; Shaohuai Shi; Xin He; Bo Han 003; Xiaowen Chu 001 (ICML, 2022)

NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension. - Xin He; Jiangchao Yao; Yuxin Wang 003; Zhenheng Tang; Ka Chun Cheung; Simon See; Bo Han 003; Xiaowen Chu 001 (AAAI, 2023)

FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training. - Zhenheng Tang; Xiaowen Chu 001; Ryan Yide Ran; Sunwoo Lee 001; Shaohuai Shi; Yonggang Zhang 003; Yuxin Wang 003; Alex Qiaozhong Liang; Salman Avestimehr; Chaoyang He 001 (CoRR, 2023)

FusionAI: Decentralized Training and Deploying LLMs with Massive Consumer-Level GPUs. - Zhenheng Tang; Yuxin Wang 003; Xin He; Longteng Zhang; Xinglin Pan; Qiang Wang 022; Rongfei Zeng; Kaiyong Zhao; Shaohuai Shi; Bingsheng He; Xiaowen Chu 001 (CoRR, 2023)

Reliable and Efficient In-Memory Fault Tolerance of Large Language Model Pretraining. - Yuxin Wang 003; Shaohuai Shi; Xin He; Zhenheng Tang; Xinglin Pan; Yang Zheng; Xiaoyu Wu; Amelie Chi Zhou; Bingsheng He; Xiaowen Chu 001 (CoRR, 2023)

GossipFL: A Decentralized Federated Learning Framework With Sparsified and Adaptive Communication. - Zhenheng Tang; Shaohuai Shi; Bo Li 001; Xiaowen Chu 001 (IEEE Trans. Parallel Distributed Syst., 2023)

VMRNN: Integrating Vision Mamba and LSTM for Efficient and Accurate Spatiotemporal Forecasting. - Yujin Tang; Peijie Dong; Zhenheng Tang; Xiaowen Chu 001; Junwei Liang 001 (CVPR Workshops, 2024)

LPZero: Language Model Zero-cost Proxy Search from Zero. - Peijie Dong; Lujun Li 001; Xiang Liu 001; Zhenheng Tang; Xuebo Liu 002; Qiang Wang 022; Xiaowen Chu 001 (EMNLP (Findings), 2024)

FedImpro: Measuring and Improving Client Update in Federated Learning. - Zhenheng Tang; Yonggang Zhang 003; Shaohuai Shi; Xinmei Tian 001; Tongliang Liu; Bo Han 003; Xiaowen Chu 001 (ICLR, 2024)

Pruner-Zero: Evolving Symbolic Pruning Metric From Scratch for Large Language Models. - Peijie Dong; Lujun Li 001; Zhenheng Tang; Xiang Liu 001; Xinglin Pan; Qiang Wang 022; Xiaowen Chu 001 (ICML, 2024)

Bandwidth-Aware and Overlap-Weighted Compression for Communication-Efficient Federated Learning. - Zichen Tang; Junlin Huang; Rudan Yan; Yuxin Wang 003; Zhenheng Tang; Shaohuai Shi; Amelie Chi Zhou; Xiaowen Chu 001 (ICPP, 2024)

Discovering Sparsity Allocation for Layer-wise Pruning of Large Language Models. - Lujun Li 001; Peijie Dong; Zhenheng Tang; Xiang Liu 001; Qiang Wang 022; Wenhan Luo; Wei Xue 002; Qifeng Liu; Xiaowen Chu 001; Yike Guo (NeurIPS, 2024)

Should We Really Edit Language Models? On the Evaluation of Edited Language Models. - Qi Li; Xiang Liu 001; Zhenheng Tang; Peijie Dong; Zeyu Li; Xinglin Pan; Xiaowen Chu 001 (NeurIPS, 2024)

FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion. - Zhenheng Tang; Yonggang Zhang 003; Peijie Dong; Yiu-ming Cheung; Amelie Chi Zhou; Bo Han 003; Xiaowen Chu 001 (NeurIPS, 2024)

Towards Efficient and Reliable LLM Serving: A Real-World Workload Study. - Yuxin Wang 003; Yuhan Chen; Zeyu Li; Zhenheng Tang; Rui Guo; Xin Wang; Qiang Wang 022; Amelie Chi Zhou; Xiaowen Chu 001 (CoRR, 2024)

STBLLM: Breaking the 1-Bit Barrier with Structured Binary LLMs. - Peijie Dong; Lujun Li 001; Dayou Du; Yuhan Chen; Zhenheng Tang; Qiang Wang 022; Wei Xue 002; Wenhan Luo; Qifeng Liu; Yike Guo; Xiaowen Chu 001 (CoRR, 2024)

Enhancing LLM Trading Performance with Fact-Subjectivity Aware Reasoning. - Qian Wang 002; Yuchen Gao; Zhenheng Tang; Bingqiao Luo; Bingsheng He (CoRR, 2024)

FusionLLM: A Decentralized LLM Training System on Geo-distributed GPUs with Adaptive Compression. - Zhenheng Tang; Xueze Kang; Yiming Yin; Xinglin Pan; Yuxin Wang 003; Xin He; Qiang Wang 022; Rongfei Zeng; Kaiyong Zhao; Shaohuai Shi; Amelie Chi Zhou; Bo Li 001; et al. (CoRR, 2024)

ExpertFlow: Optimized Expert Activation and Token Allocation for Efficient Mixture-of-Experts Inference. - Xin He; Shunkang Zhang; Yuxin Wang 003; Haiyan Yin; Zihao Zeng; Shaohuai Shi; Zhenheng Tang; Xiaowen Chu 001; Ivor W. Tsang; Yew-Soon Ong (CoRR, 2024)

ParZC: Parametric Zero-Cost Proxies for Efficient NAS. - Peijie Dong; Lujun Li 001; Zhenheng Tang; Xiang Liu 001; Zimian Wei; Qiang Wang 022; Xiaowen Chu 001 (AAAI, 2025)

MegaAgent: A Large-Scale Autonomous LLM-based Multi-Agent System Without Predefined SOPs. - Qian Wang 002; Tianyu Wang; Zhenheng Tang; Qinbin Li; Nuo Chen 002; Jingsheng Liang; Bingsheng He (ACL (Findings), 2025)

FSMoE: A Flexible and Scalable Training System for Sparse Mixture-of-Experts Models. - Xinglin Pan; Wenxiang Lin; Lin Zhang; Shaohuai Shi; Zhenheng Tang; Rui Wang; Bo Li 001; Xiaowen Chu 001 (ASPLOS (1), 2025)

STBLLM: Breaking the 1-Bit Barrier with Structured Binary LLMs. - Peijie Dong; Lujun Li 001; Yuedong Zhong; Dayou Du; Ruibo Fan; Yuhan Chen; Zhenheng Tang; Qiang Wang 022; Wei Xue 002; Yike Guo; Xiaowen Chu 001 (ICLR, 2025)

Hot-pluggable Federated Learning: Bridging General and Personalized FL via Dynamic Selection. - Lei Shen; Zhenheng Tang; Lijun Wu; Yonggang Zhang 003; Xiaowen Chu 001; Tao Qin; Bo Han 003 (ICLR, 2025)

What Limits LLM-based Human Simulation: LLMs or Our Design? - Qian Wang 002; Jiaying Wu; Zhenheng Tang; Bingqiao Luo; Nuo Chen 002; Wei Chen; Bingsheng He (CoRR, 2025)

ChunkKV: Semantic-Preserving KV Cache Compression for Efficient Long-Context LLM Inference. - Xiang Liu 001; Zhenheng Tang; Peijie Dong; Zeyu Li; Bo Li 001; Xuming Hu; Xiaowen Chu 001 (CoRR, 2025)

Can LLMs Maintain Fundamental Abilities under KV Cache Compression? - Xiang Liu 001; Zhenheng Tang; Hong Chen; Peijie Dong; Zeyu Li; Xiuze Zhou; Bo Li 001; Xuming Hu; Xiaowen Chu 001 (CoRR, 2025)

Mediator: Memory-efficient LLM Merging with Less Parameter Conflicts and Uncertainty Based Routing. - Kunfeng Lai; Zhenheng Tang; Xinglin Pan; Peijie Dong; Xiang Liu 001; Haolan Chen; Li Shen 005; Bo Li 001; Xiaowen Chu 001 (CoRR, 2025)

One-shot Federated Learning Methods: A Practical Guide. - Xiang Liu 017; Zhenheng Tang; Xia Li 005; Yijun Song; Sijie Ji; Zemin Liu; Bo Han 003; Linshan Jiang; Jialin Li 001 (CoRR, 2025)

DreamDDP: Accelerating Data Parallel Distributed LLM Training with Layer-wise Scheduled Partial Synchronization. - Zhenheng Tang; Zichen Tang; Junlin Huang; Xinglin Pan; Rudan Yan; Yuxin Wang 003; Amelie Chi Zhou; Shaohuai Shi; Xiaowen Chu 001; Bo Li 001 (CoRR, 2025)

The Lottery LLM Hypothesis, Rethinking What Abilities Should LLM Compression Preserve? - Zhenheng Tang; Xiang Liu 001; Qian Wang 002; Peijie Dong; Bingsheng He; Xiaowen Chu 001; Bo Li 001 (CoRR, 2025)

From ChatGPT to DeepSeek: Can LLMs Simulate Humanity? - Qian Wang 002; Zhenheng Tang; Bingsheng He (CoRR, 2025)

Assessing Judging Bias in Large Reasoning Models: An Empirical Study. - Qian Wang 002; Zhanzhi Lou; Zhenheng Tang; Nuo Chen 002; Xuandong Zhao; Wenxuan Zhang; Dawn Song; Bingsheng He (CoRR, 2025)

Can Compressed LLMs Truly Act? An Empirical Evaluation of Agentic Capabilities in LLM Compression. - Peijie Dong; Zhenheng Tang; Xiang Liu 001; Lujun Li 001; Xiaowen Chu 001; Bo Li 001 (CoRR, 2025)

AnTKV: Anchor Token-Aware Sub-Bit Vector Quantization for KV Cache in Large Language Models. - Zeyu Li; Chuanfu Xiao; Yang Wang; Xiang Liu 001; Zhenheng Tang; Baotong Lu; Mao Yang; Xinyu Chen; Xiaowen Chu 001 (CoRR, 2025)

Reasoning Models Can be Easily Hacked by Fake Reasoning Bias. - Qian Wang 002; Yubo Fan; Zhenheng Tang; Nuo Chen 002; Wenxuan Wang; Bingsheng He (CoRR, 2025)

RouteMark: A Fingerprint for Intellectual Property Attribution in Routing-based Model Merging. - Xin He; Junxi Shen; Zhenheng Tang; Xiaowen Chu 001; Bo Li 001; Ivor W. Tsang; Yew-Soon Ong (CoRR, 2025)