Value-Aware Resampling and Loss for Imbalanced Classification. - Li Sun; Jie Song 011; Cheng Hua; Chengchao Shen; Mingli Song (CSAE, 2018)

Transductive Unbiased Embedding for Zero-Shot Learning. - Jie Song 011; Chengchao Shen; Yezhou Yang; Yang Liu 212; Mingli Song (CVPR, 2018)

Selective Zero-Shot Classification with Augmented Attributes. - Jie Song 011; Chengchao Shen; Jie Lei 002; Anxiang Zeng; Kairi Ou; Dacheng Tao; Mingli Song (ECCV (9), 2018)

DeepSIC: Deep Semantic Image Compression. - Sihui Luo 001; Yezhou Yang; Yanling Yin; Chengchao Shen; Ya Zhao; Mingli Song (ICONIP (1), 2018)

Intra-class Structure Aware Networks for Screen Defect Detection. - Chengchao Shen; Jie Song 011; Shuyi Song; Sihui Luo 001; Li Sun; Mingli Song (ICONIP (4), 2018)

Reliability Aware Web Accessibility Experience Metric. - Shuyi Song; Jiajun Bu; Chengchao Shen; Andreas Artmeier; Zhi Yu; Qin Zhou (W4A, 2018)

Amalgamating Knowledge towards Comprehensive Classification. - Chengchao Shen; Xinchao Wang; Jie Song 011; Li Sun; Mingli Song (AAAI, 2019)

Customizing Student Networks From Heterogeneous Teachers via Adaptive Knowledge Amalgamation. - Chengchao Shen; Mengqi Xue; Xinchao Wang; Jie Song 011; Li Sun; Mingli Song (ICCV, 2019)

Deep Model Transferability from Attribution Maps. - Jie Song 011; Yixin Chen; Xinchao Wang; Chengchao Shen; Mingli Song (NeurIPS, 2019)

Data-Free Adversarial Distillation. - Gongfan Fang; Jie Song 011; Chengchao Shen; Xinchao Wang; Da Chen; Mingli Song (CoRR, 2019)

DEPARA: Deep Attribution Graph for Deep Knowledge Transferability. - Jie Song 011; Yixin Chen; Jingwen Ye; Xinchao Wang; Chengchao Shen; Feng Mao; Mingli Song (CVPR, 2020)

Progressive Network Grafting for Few-Shot Knowledge Distillation. - Chengchao Shen; Xinchao Wang; Youtan Yin; Jie Song 011; Sihui Luo 001; Mingli Song (AAAI, 2021)

Training Generative Adversarial Networks in One Stage. - Chengchao Shen; Youtan Yin; Xinchao Wang; Xubin Li; Jie Song 011; Mingli Song (CVPR, 2021)

Learning Dynamic Preference Structure Embedding From Temporal Networks. - Tongya Zheng; Zunlei Feng; Yu Wang 176; Chengchao Shen; Mingli Song; Xingen Wang; Xinyu Wang 001; Chun Chen 001; Hao Xu (ICBK, 2021)

Contrastive Model Invertion for Data-Free Knolwedge Distillation. - Gongfan Fang; Jie Song 011; Xinchao Wang; Chengchao Shen; Xingen Wang; Mingli Song (IJCAI, 2021)

Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data. - Gongfan Fang; Yifan Bao; Jie Song 011; Xinchao Wang; Donglin Xie; Chengchao Shen; Mingli Song (NeurIPS, 2021)

Contrastive Model Inversion for Data-Free Knowledge Distillation. - Gongfan Fang; Jie Song 011; Xinchao Wang; Chengchao Shen; Xingen Wang; Mingli Song (CoRR, 2021)

MVSF: Multi-View Signature Fusion Network for Noninvasively Predicting Ki67 Status. - Xinyu Li; Jianhong Cheng; Jin Liu 012; Hulin Kuang; Chengchao Shen; Pei Yang; Jianxin Wang 001 (BIBM, 2022)

Modeling Global Distribution for Federated Learning with Label Distribution Skew. - Tao Sheng; Chengchao Shen; Yuan Liu; Yeyu Ou; Zhe Qu; Jianxin Wang 001 (CoRR, 2022)

Improving Medical Image Denoising via a Lightweight Plug-and-play Module. - Lei Ma; Hulin Kuang; Jin Liu 012; Chengchao Shen; Jianxin Wang 001 (BIBM, 2023)

How to Prevent the Poor Performance Clients for Personalized Federated Learning? - Zhe Qu; Xingyu Li; Xiao Han; Rui Duan; Chengchao Shen; Lixing Chen (CVPR, 2023)

Inter-Instance Similarity Modeling for Contrastive Learning. - Chengchao Shen; Dawei Liu; Hao Tang; Zhe Qu; Jianxin Wang 001 (CoRR, 2023)

Modeling global distribution for federated learning with label distribution skew. - Tao Sheng; Chengchao Shen; Yuan Liu; Yeyu Ou; Zhe Qu; Yixiong Liang; Jianxin Wang 001 (Pattern Recognit., 2023)

Multi-Grained Contrast for Data-Efficient Unsupervised Representation Learning. - Chengchao Shen; Jianzhong Chen; Jianxin Wang 001 (CoRR, 2024)

A unified Personalized Federated Learning framework ensuring Domain Generalization. - Yuan Liu; Zhe Qu; Shu Wang; Chengchao Shen; Yixiong Liang; Jianxin Wang 001 (Expert Syst. Appl., 2025)

Multi-grained contrast for data-efficient unsupervised representation learning. - Chengchao Shen; Jianzhong Chen; Jianxin Wang (Pattern Recognit., 2025)

Asymmetric patch sampling for contrastive learning. - Chengchao Shen; Jianzhong Chen; Shu Wang; Hulin Kuang; Jin Liu 012; Jianxin Wang 001 (Pattern Recognit., 2025)

Data-efficient multi-scale fusion vision transformer. - Hao Tang; Dawei Liu; Chengchao Shen (Pattern Recognit., 2025)

Learning Compact Vision Tokens for Efficient Large Multimodal Models. - Hao Tang; Chengchao Shen (CoRR, 2025)

Multiple Object Stitching for Unsupervised Representation Learning. - Chengchao Shen; Dawei Liu; Jian-Xin Wang 001 (CoRR, 2025)

Diversity-Guided MLP Reduction for Efficient Large Vision Transformers. - Chengchao Shen; Hourun Zhu; Gongfan Fang; Jianxin Wang; Xinchao Wang (CoRR, 2025)

SDMPrune: Self-Distillation MLP Pruning for Efficient Large Language Models. - Hourun Zhu; Chengchao Shen (CoRR, 2025)