Floating-point mixed-radix FFT core generation for FPGA and comparison with GPU and CPU. - Bo Duan; Wendi Wang 002; Xingjian Li 002; Chunming Zhang; Peiheng Zhang; Ninghui Sun (FPT, 2011)

Experience of parallelizing cryo-EM 3D reconstruction on a CPU-GPU heterogeneous system. - Linchuan Li; Xingjian Li 002; Guangming Tan; Mingyu Chen 001; Peiheng Zhang (HPDC, 2011)

Biprominer: Automatic Mining of Binary Protocol Features. - Yipeng Wang 001; Xingjian Li 002; Jiao Meng; Yong Zhao; Zhibin Zhang; Li Guo 001 (PDCAT, 2011)

An optimized large-scale hybrid DGEMM design for CPUs and ATI GPUs. - Jiajia Li 001; Xingjian Li 002; Guangming Tan; Mingyu Chen 001; Ninghui Sun (ICS, 2012)

Towards Making Deep Transfer Learning Never Hurt. - Ruosi Wan; Haoyi Xiong; Xingjian Li 002; Zhanxing Zhu; Jun Huan (ICDM, 2019)

Delta: Deep Learning Transfer using Feature Map with Attention for Convolutional Networks. - Xingjian Li 002; Haoyi Xiong; Hanchao Wang; Yuxuan Rao; Liping Liu; Jun Huan (ICLR (Poster), 2019)

An Empirical Study on Regularization of Deep Neural Networks by Local Rademacher Complexity. - Yingzhen Yang; Xingjian Li 002; Jun Huan (CoRR, 2019)

Quasi-optimal Data Placement for Secure Multi-tenant Data Federation on the Cloud. - Qi Kang; Ji Liu 003; Sijia Yang; Haoyi Xiong; Haozhe An; Xingjian Li 002; Zhi Feng; Licheng Wang; Dejing Dou (IEEE BigData, 2020)

Neighbours Matter: Image Captioning with Similar Images. - Qingzhong Wang; Jiuniu Wang; Antoni B. Chan; Siyu Huang; Haoyi Xiong; Xingjian Li 002; Dejing Dou (BMVC, 2020)

Pay Attention to Features, Transfer Learn Faster CNNs. - Kafeng Wang; Xitong Gao; Yiren Zhao; Xingjian Li 002; Dejing Dou; Cheng-Zhong Xu 001 (ICLR, 2020)

RIFLE: Backpropagation in Depth for Deep Transfer Learning through Re-Initializing the Fully-connected LayEr. - Xingjian Li 002; Haoyi Xiong; Haozhe An; Cheng-Zhong Xu 001; Dejing Dou (ICML, 2020)

XMixup: Efficient Transfer Learning with Auxiliary Samples by Cross-domain Mixup. - Xingjian Li 002; Haoyi Xiong; Haozhe An; Chengzhong Xu 001; Dejing Dou (CoRR, 2020)

Measuring Information Transfer in Neural Networks. - Xiao Zhang 001; Xingjian Li 002; Dejing Dou; Ji Wu 002 (CoRR, 2020)

Towards Accurate Knowledge Transfer via Target-awareness Representation Disentanglement. - Xingjian Li 002; Di Hu 001; Xuhong Li 002; Haoyi Xiong; Zhi Ye; Zhipeng Wang; Chengzhong Xu 001; Dejing Dou (CoRR, 2020)

Temporal Relational Modeling with Self-Supervision for Action Segmentation. - Dong Wang 028; Di Hu 001; Xingjian Li 002; Dejing Dou (AAAI, 2021)

Adaptive Consistency Regularization for Semi-Supervised Transfer Learning. - Abulikemu Abuduweili; Xingjian Li 002; Humphrey Shi; Cheng-Zhong Xu 001; Dejing Dou (CVPR, 2021)

Elastic Deep Learning Using Knowledge Distillation with Heterogeneous Computing Resources. - Daxiang Dong; Ji Liu 003; Xi Wang; Weibao Gong; An Qin 001; Xingjian Li 002; Dianhai Yu; Patrick Valduriez; Dejing Dou (Euro-Par Workshops, 2021)

Noise Stability Regularization for Improving BERT Fine-tuning. - Hang Hua; Xingjian Li 002; Dejing Dou; Cheng-Zhong Xu 001; Jiebo Luo 001 (NAACL-HLT, 2021)

Interpretable Deep Learning: Interpretations, Interpretability, Trustworthiness, and Beyond. - Xuhong Li 002; Haoyi Xiong; Xingjian Li 002; Xuanyu Wu; Xiao Zhang 001; Ji Liu 003; Jiang Bian 003; Dejing Dou (CoRR, 2021)

SMILE: Self-Distilled MIxup for Efficient Transfer LEarning. - Xingjian Li 002; Haoyi Xiong; Chengzhong Xu 001; Dejing Dou (CoRR, 2021)

Improving Adversarial Robustness via Attention and Adversarial Logit Pairing. - Xingjian Li 002; Dou Goodman; Ji Liu 003; Tao Wei; Dejing Dou (Frontiers Artif. Intell., 2021)

"In-Network Ensemble": Deep Ensemble Learning with Diversified Knowledge Distillation. - Xingjian Li 002; Haoyi Xiong; Zeyu Chen; Jun Huan; Cheng-Zhong Xu 001; Dejing Dou (ACM Trans. Intell. Syst. Technol., 2021)

Boosting Active Learning via Improving Test Performance. - Tianyang Wang; Xingjian Li 002; Pengkun Yang; Guosheng Hu; Xiangrui Zeng; Siyu Huang; Cheng-Zhong Xu 001; Min Xu 009 (AAAI, 2022)

Inadequately Pre-trained Models are Better Feature Extractors. - Andong Deng; Xingjian Li 002; Zhibing Li; Di Hu 001; Chengzhong Xu 001; Dejing Dou (CoRR, 2022)

Deep Active Learning with Noise Stability. - Xingjian Li 002; Pengkun Yang; Tianyang Wang; Xueying Zhan; Min Xu 009; Dejing Dou; Chengzhong Xu 001 (CoRR, 2022)

Fine-tuning Pre-trained Language Models with Noise Stability Regularization. - Hang Hua; Xingjian Li 002; Dejing Dou; Cheng-Zhong Xu 001; Jiebo Luo 001 (CoRR, 2022)

InterpretDL: Explaining Deep Models in PaddlePaddle. - Xuhong Li 002; Haoyi Xiong; Xingjian Li 002; Xuanyu Wu; Zeyu Chen; Dejing Dou (J. Mach. Learn. Res., 2022)

Interpretable deep learning: interpretation, interpretability, trustworthiness, and beyond. - Xuhong Li 002; Haoyi Xiong; Xingjian Li 002; Xuanyu Wu; Xiao Zhang 001; Ji Liu 003; Jiang Bian 003; Dejing Dou (Knowl. Inf. Syst., 2022)

COLAM: Co-Learning of Deep Neural Networks and Soft Labels via Alternating Minimization. - Xingjian Li 002; Haoyi Xiong; Haozhe An; Cheng-Zhong Xu 001; Dejing Dou (Neural Process. Lett., 2022)

Knowledge Distillation with Attention for Deep Transfer Learning of Convolutional Networks. - Xingjian Li 002; Haoyi Xiong; Zeyu Chen; Jun Huan; Ji Liu 003; Cheng-Zhong Xu 001; Dejing Dou (ACM Trans. Knowl. Discov. Data, 2022)

GrOD: Deep Learning with Gradients Orthogonal Decomposition for Knowledge Transfer, Distillation, and Adversarial Training. - Haoyi Xiong; Ruosi Wan; Jian Zhao 006; Zeyu Chen; Xingjian Li 002; Zhanxing Zhu; Jun Huan (ACM Trans. Knowl. Discov. Data, 2022)

Improving Bert Fine-Tuning via Stabilizing Cross-Layer Mutual Information. - Jicun Li; Xingjian Li 002; Tianyang Wang; Shi Wang 002; Yanan Cao 001; Cheng-Zhong Xu 001; Dejing Dou (ICASSP, 2023)

Towards Inadequately Pre-trained Models in Transfer Learning. - Andong Deng; Xingjian Li 002; Di Hu 001; Tianyang Wang; Haoyi Xiong; Cheng-Zhong Xu 001 (ICCV, 2023)

Overcoming Catastrophic Forgetting for Fine-Tuning Pre-trained GANs. - Zeren Zhang; Xingjian Li 002; Tao Hong; Tianyang Wang; Jinwen Ma; Haoyi Xiong; Cheng-Zhong Xu 001 (ECML/PKDD (5), 2023)

G-LIME: Statistical learning for local interpretations of deep neural networks using global priors. - Xuhong Li 002; Haoyi Xiong; Xingjian Li 002; Xiao Zhang 001; Ji Liu 003; Haiyan Jiang; Zeyu Chen; Dejing Dou (Artif. Intell., 2023)

Large-scale knowledge distillation with elastic heterogeneous computing resources. - Ji Liu 003; Daxiang Dong; Xi Wang; An Qin 001; Xingjian Li 002; Patrick Valduriez; Dejing Dou; Dianhai Yu (Concurr. Comput. Pract. Exp., 2023)

Robust Cross-Modal Knowledge Distillation for Unconstrained Videos. - Wenke Xia; Xingjian Li 002; Andong Deng; Haoyi Xiong; Dejing Dou; Di Hu 001 (CoRR, 2023)

SMILE: Sample-to-feature Mixup for Efficient Transfer Learning. - Xingjian Li 002; Haoyi Xiong; Cheng-Zhong Xu 001; Dejing Dou (Trans. Mach. Learn. Res., 2023)

Semi-supervised transfer learning with hierarchical self-regularization. - Xingjian Li 002; Abulikemu Abuduweili; Humphrey Shi; Pengkun Yang; Dejing Dou; Haoyi Xiong; Chengzhong Xu 001 (Pattern Recognit., 2023)

G-LIME: Statistical Learning for Local Interpretations of Deep Neural Networks Using Global Priors (Abstract Reprint). - Xuhong Li 002; Haoyi Xiong; Xingjian Li 002; Xiao Zhang 001; Ji Liu 003; Haiyan Jiang; Zeyu Chen; Dejing Dou (AAAI, 2024)

Deep Active Learning with Noise Stability. - Xingjian Li 002; Pengkun Yang; Yangcheng Gu; Xueying Zhan; Tianyang Wang; Min Xu 009; Chengzhong Xu 001 (AAAI, 2024)

Geometry-Guided Conditional Adaptation for Surrogate Models of Large-Scale 3D PDEs on Arbitrary Geometries. - Jingyang Deng; Xingjian Li 002; Haoyi Xiong; Xiaoguang Hu; Jinwen Ma (IJCAI, 2024)

Towards accurate knowledge transfer via target-awareness representation disentanglement. - Xingjian Li 002; Di Hu 001; Xuhong Li 002; Haoyi Xiong; Cheng-Zhong Xu 001; Dejing Dou (Mach. Learn., 2024)

Vox-UDA: Voxel-wise Unsupervised Domain Adaptation for Cryo-Electron Subtomogram Segmentation with Denoised Pseudo-Labeling. - Haoran Li; Xingjian Li 002; Jiahua Shi; Huaming Chen; Bo Du 004; Daisuke Kihara; Johan Barthélemy; Jun Shen 001; Min Xu 009 (AAAI, 2025)

BOE-ViT: Boosting Orientation Estimation with Equivariance in Self-Supervised 3D Subtomogram Alignment. - Runmin Jiang; Jackson Daggett; Shriya Pingulkar; Yizhou Zhao; Priyanshu Dhingra; Daniel Brown; Qifeng Wu; Xiangrui Zeng; Xingjian Li 002; Min Xu 009 (CVPR, 2025)

DiffCAM: Data-Driven Saliency Maps by Capturing Feature Differences. - Xingjian Li 002; Qiming Zhao; Neelesh Bisht; Mostofa Rafid Uddin; Jin Yu Kim; Bryan Zhang; Min Xu 009 (CVPR, 2025)

Multimodal Generalized Category Discovery. - Yuchang Su; Renping Zhou; Siyu Huang; Xingjian Li 002; Tianyang Wang; Ziyue Wang; Min Xu 009 (CVPR Workshops, 2025)

Fetal-BCP: Addressing Empirical Distribution Gap in Semi-Supervised Fetal Ultrasound Segmentation. - Ha-Hieu Pham; Tran Quoc Khanh Le; Hoang-Thien Nguyen; Nguyen Lan Vi Vu; Quang-Vinh Dinh; Thanh-Huy Nguyen; Xingjian Li 002; Min Xu 009 (ISBI, 2025)

Improving Pretrained Language Model Fine-Tuning With Noise Stability Regularization. - Hang Hua; Xingjian Li 002; Dejing Dou; Cheng-Zhong Xu 001; Jiebo Luo 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)

Visual Variational Autoencoder Prompt Tuning. - Xi Xiao; Yunbei Zhang; Yanshuh Li; Xingjian Li 002; Tianyang Wang; Jihun Hamm; Xiao Wang 004; Min Xu 009 (CoRR, 2025)

Trustworthy federated learning: privacy, security, and beyond. - Chunlu Chen; Ji Liu 003; Haowen Tan; Xingjian Li 002; Kevin I-Kai Wang; Peng Li 017; Kouichi Sakurai; Dejing Dou (Knowl. Inf. Syst., 2025)

Describe Anything in Medical Images. - Xi Xiao; Yunbei Zhang; Thanh-Huy Nguyen; Ba Thinh Lam; Janet Wang; Lin Zhao; Jihun Hamm; Tianyang Wang; Xingjian Li 002; Xiao Wang 004; Hao Xu; Tianming Liu; et al. (CoRR, 2025)

AutoMiSeg: Automatic Medical Image Segmentation via Test-Time Adaptation of Foundation Models. - Xingjian Li 002; Qifeng Wu; Colleen Que; Yiran Ding; Adithya S. Ubaradka; Jianhua Xing; Tianyang Wang; Min Xu 009 (CoRR, 2025)

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection. - Gokul Adethya T; Bhanu Pratyush Mantha; Tianyang Wang; Xingjian Li 002; Min Xu 009 (CoRR, 2025)

CryoCCD: Conditional Cycle-consistent Diffusion with Biophysical Modeling for Cryo-EM Synthesis. - Runmin Jiang; Genpei Zhang; Yuntian Yang; Siqi Wu; Yuheng Zhang; Wanyue Feng; Yizhou Zhao; Xi Xiao; Xiao Wang 004; Tianyang Wang; Xingjian Li 002; Min Xu 009 (CoRR, 2025)

Visual Instance-aware Prompt Tuning. - Xi Xiao; Yunbei Zhang; Xingjian Li 002; Tianyang Wang; Xiao Wang 004; Yuxiang Wei; Jihun Hamm; Min Xu 009 (CoRR, 2025)