InvisibleFL: Federated Learning over Non-Informative Intermediate Updates against Multimedia Privacy Leakages. - Qiushi Li; Wenwu Zhu 001; Chao Wu 002; Xinglin Pan; Fan Yang 024; Yuezhi Zhou; Yaoxue Zhang (ACM Multimedia, 2020)

LdsConv: Learned Depthwise Separable Convolutions by Group Pruning. - Wenxiang Lin; Yan Ding 003; Hua-Liang Wei; Xinglin Pan; Yutong Zhang (Sensors, 2020)

AFINet: Attentive Feature Integration Networks for Image Classification. - Xinglin Pan; Jing Xu; Yu Pan 005; Liangjian Wen; Wenxiang Lin; Kun Bai; Zenglin Xu (CoRR, 2021)

Exploring Category-correlated Feature for Few-shot Image Classification. - Jing Xu; Xinglin Pan; Xu Luo 003; Wenjie Pei; Zenglin Xu (CoRR, 2021)

ENIGMA: Low-Latency and Privacy-Preserving Edge Inference on Heterogeneous Neural Network Accelerators. - Qiushi Li; Ju Ren 001; Xinglin Pan; Yuezhi Zhou; Yaoxue Zhang (ICDCS, 2022)

Alleviating the Sample Selection Bias in Few-shot Learning by Removing Projection to the Centroid. - Jing Xu; Xu Luo 003; Xinglin Pan; Yanan Li; Wenjie Pei; Zenglin Xu (NeurIPS, 2022)

AFINet: Attentive Feature Integration Networks for image classification. - Xinglin Pan; Jing Xu; Yu Pan 005; Liangjian Wen; Wenxiang Lin; Kun Bai; Hongguang Fu; Zenglin Xu (Neural Networks, 2022)

Generalized Category Discovery with Clustering Assignment Consistency. - Xiangli Yang; Xinglin Pan; Irwin King; Zenglin Xu (ICONIP (5), 2023)

PipeMoE: Accelerating Mixture-of-Experts through Adaptive Pipelining. - Shaohuai Shi; Xinglin Pan; Xiaowen Chu 001; Bo Li 001 (INFOCOM, 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)

Dissecting the Runtime Performance of the Training, Fine-tuning, and Inference of Large Language Models. - Longteng Zhang; Xiang Liu 001; Zeyu Li; Xinglin Pan; Peijie Dong; Ruibo Fan; Rui Guo; Xin Wang; Qiong Luo 001; Shaohuai Shi; Xiaowen Chu 001 (CoRR, 2023)

RegNet: Self-Regulated Network for Image Classification. - Jing Xu; Yu Pan 005; Xinglin Pan; Steven C. H. Hoi; Zhang Yi 001; Zenglin Xu (IEEE Trans. Neural Networks Learn. Syst., 2023)

Multi-behavior recommendation based on intent learning. - Xinglin Pan; Mingxin Gan (Multim. Syst., 2023)

Multi-task Domain Adaptation for Language Grounding with 3D Objects. - Penglei Sun; Yaoxian Song; Xinglin Pan; Peijie Dong; Xiaofei Yang 002; Qiang Wang 022; Zhixu Li; Tiefeng Li; Xiaowen Chu 001 (ECCV (34), 2024)

ScheMoE: An Extensible Mixture-of-Experts Distributed Training System with Tasks Scheduling. - Shaohuai Shi; Xinglin Pan; Qiang Wang 022; Chengjian Liu; Xiaozhe Ren; Zhongzhe Hu; Yu Yang; Bo Li 001; Xiaowen Chu 001 (EuroSys, 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)

Parm: Efficient Training of Large Sparsely-Activated Models with Dedicated Schedules. - Xinglin Pan; Wenxiang Lin; Shaohuai Shi; Xiaowen Chu 001; Weinong Sun; Bo Li 001 (INFOCOM, 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)

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

Task Scheduling for Efficient Inference of Large Language Models on Single Moderate GPU Systems. - Wenxiang Lin; Xinglin Pan; Shaohuai Shi; Xuan Wang 002; Xiaowen Chu 001 (CoRR, 2024)

Predicting intubation for intensive care units patients: A deep learning approach to improve patient management. - Ruixi Li; Zenglin Xu; Jing Xu; Xinglin Pan; Hong Wu; Xiaobo Huang; Mengling Feng (Int. J. Medical Informatics, 2024)

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)

ScheInfer: Efficient Inference of Large Language Models with Task Scheduling on Moderate GPUs. - Wenxiang Lin; Xinglin Pan; Shaohuai Shi; Xuan Wang 002; Xiaowen Chu 001 (Euro-Par (3), 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)

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)

CORE: CORrelation-Guided Feature Enhancement for Few-Shot Image Classification. - Jing Xu; Xinglin Pan; Jingquan Wang; Wenjie Pei; Qing Liao 001; Zenglin Xu (IEEE Trans. Neural Networks Learn. Syst., 2025)

HierMoE: Accelerating MoE Training with Hierarchical Token Deduplication and Expert Swap. - Wenxiang Lin; Xinglin Pan; Lin Zhang; Shaohuai Shi; Xuan Wang 002; Xiaowen Chu 001 (CoRR, 2025)