A general neural framework for classification rule mining. - Zhi-Hua Zhou; Yuan Jiang 001; Shifu Chen (Int. J. Comput. Syst. Signals, 2000)

Genetic Algorithm based Selective Neural Network Ensemble. - Zhi-Hua Zhou; Jianxin Wu 001; Yuan Jiang 001; Shifu Chen (IJCAI, 2001)

The Application of Visualization and Neural Network Techniques in a Power Transformer Condition Monitoring System. - Zhi-Hua Zhou; Yuan Jiang 001; Xu-Ri Yin; Shifu Chen (IEA/AIE, 2002)

Lung cancer cell identification based on artificial neural network ensembles. - Zhi-Hua Zhou; Yuan Jiang 001; Yu-Bin Yang; Shifu Chen (Artif. Intell. Medicine, 2002)

SOM Based Image Segmentation. - Yuan Jiang 001; Kejia Chen 001; Zhi-Hua Zhou (RSFDGrC, 2003)

Extracting symbolic rules from trained neural network ensembles. - Zhi-Hua Zhou; Yuan Jiang 001; Shifu Chen (AI Commun., 2003)

Medical diagnosis with C4.5 rule preceded by artificial neural network ensemble. - Zhi-Hua Zhou; Yuan Jiang 001 (IEEE Trans. Inf. Technol. Biomed., 2003)

Exploiting Unlabeled Data in Content-Based Image Retrieval. - Zhi-Hua Zhou; Ke-Jia Chen 001; Yuan Jiang 001 (ECML, 2004)

Editing Training Data for kNN Classifiers with Neural Network Ensemble. - Yuan Jiang 001; Zhi-Hua Zhou (ISNN (1), 2004)

SOM Ensemble-Based Image Segmentation. - Yuan Jiang 001; Zhi-Hua Zhou (Neural Process. Lett., 2004)

NeC4.5: Neural Ensemble Based C4.5. - Zhi-Hua Zhou; Yuan Jiang 001 (IEEE Trans. Knowl. Data Eng., 2004)

Locating Regions of Interest in CBIR with Multi-instance Learning Techniques. - Zhi-Hua Zhou; Xiao-Bing Xue; Yuan Jiang 001 (Australian Conference on Artificial Intelligence, 2005)

Dependency Bagging. - Yuan Jiang 001; Jinjiang Ling; Gang Li 009; Honghua Dai 001; Zhi-Hua Zhou (RSFDGrC (1), 2005)

Generation of Comprehensible Hypotheses from Gene Expression Data. - Yuan Jiang 001; Ming Li 005; Zhi-Hua Zhou (BioDM, 2006)

TEFE: A Time-Efficient Approach to Feature Extraction. - Li-Ping Liu 001; Yang Yu 001; Yuan Jiang 001; Zhi-Hua Zhou (ICDM, 2008)

Least Square Incremental Linear Discriminant Analysis. - Li-Ping Liu 001; Yuan Jiang 001; Zhi-Hua Zhou (ICDM, 2009)

Budget Semi-supervised Learning. - Zhi-Hua Zhou; Michael K. Ng 001; Qiao-Qiao She; Yuan Jiang 001 (PAKDD, 2009)

Mining extremely small data sets with application to software reuse. - Yuan Jiang 001; Ming Li 005; Zhi-Hua Zhou (Softw. Pract. Exp., 2009)

Multi-manifold Clustering. - Yong Wang; Yuan Jiang 001; Yi Wu 003; Zhi-Hua Zhou (PRICAI, 2010)

Localized K-Flats. - Yong Wang; Yuan Jiang 001; Yi Wu 003; Zhi-Hua Zhou (AAAI, 2011)

Local and Structural Consistency for Multi-Manifold Clustering. - Yong Wang; Yuan Jiang 001; Yi Wu 003; Zhi-Hua Zhou (IJCAI, 2011)

Ensemble approach based on conditional random field for multi-label image and video annotation. - Xin-Shun Xu; Yuan Jiang 001; Liang Peng; Xiangyang Xue 001; Zhi-Hua Zhou (ACM Multimedia, 2011)

Software Defect Detection with Rocus. - Yuan Jiang 001; Ming Li 005; Zhi-Hua Zhou (J. Comput. Sci. Technol., 2011)

Spectral Clustering on Multiple Manifolds. - Yong Wang; Yuan Jiang 001; Yi Wu 003; Zhi-Hua Zhou (IEEE Trans. Neural Networks, 2011)

Towards Discovering What Patterns Trigger What Labels. - Yufeng Li 008; Ju-Hua Hu; Yuan Jiang 001; Zhi-Hua Zhou (AAAI, 2012)

Disagreement-Based Multi-system Tracking. - Quannan Li; Xinggang Wang; Wei Wang 028; Yuan Jiang 001; Zhi-Hua Zhou; Zhuowen Tu (ACCV Workshops (2), 2012)

Semi-supervised multi-instance multi-label learning for video annotation task. - Xin-Shun Xu; Yuan Jiang 001; Xiangyang Xue 001; Zhi-Hua Zhou (ACM Multimedia, 2012)

Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval. - Lei Yuan 001; Alexander Woodard; Shuiwang Ji; Yuan Jiang 001; Zhi-Hua Zhou; Sudhir Kumar 001; Jieping Ye (BMC Bioinform., 2012)

Multi-Instance Multi-Label Learning with Weak Label. - Shu-Jun Yang; Yuan Jiang 001; Zhi-Hua Zhou (IJCAI, 2013)

Partial Multi-View Clustering. - Shao-Yuan Li; Yuan Jiang 001; Zhi-Hua Zhou (AAAI, 2014)

Learning with Augmented Multi-Instance View. - Yue Zhu 001; Jianxin Wu 001; Yuan Jiang 001; Zhi-Hua Zhou (ACML, 2014)

Rank Consistency based Multi-View Learning: A Privacy-Preserving Approach. - Han-Jia Ye; De-Chuan Zhan; Yuan Miao 002; Yuan Jiang 001; Zhi-Hua Zhou (CIKM, 2015)

Auxiliary Information Regularized Machine for Multiple Modality Feature Learning. - Yang Yang 074; Han-Jia Ye; De-Chuan Zhan; Yuan Jiang 001 (IJCAI, 2015)

Multi-label Selective Ensemble. - Nan Li 019; Yuan Jiang 001; Zhi-Hua Zhou (MCS, 2015)

Multi-Label Active Learning from Crowds. - Shao-Yuan Li; Yuan Jiang 001; Zhi-Hua Zhou (CoRR, 2015)

Pairwised Specific Distance Learning from Physical Linkages. - Ju-Hua Hu; De-Chuan Zhan; Xintao Wu; Yuan Jiang 001; Zhi-Hua Zhou (ACM Trans. Knowl. Discov. Data, 2015)

Instance Specific Metric Subspace Learning: A Bayesian Approach. - Han-Jia Ye; De-Chuan Zhan; Yuan Jiang 001 (AAAI, 2016)

Learning Feature Aware Metric. - Han-Jia Ye; De-Chuan Zhan; Xue-Min Si; Yuan Jiang 001 (ACML, 2016)

College Student Scholarships and Subsidies Granting: A Multi-modal Multi-label Approach. - Han-Jia Ye; De-Chuan Zhan; Xiaolin Li; Zhen-Chuan Huang; Yuan Jiang 001 (ICDM, 2016)

Learning by Actively Querying Strong Modal Features. - Yang Yang 074; De-Chuan Zhan; Yuan Jiang 001 (IJCAI, 2016)

What Makes Objects Similar: A Unified Multi-Metric Learning Approach. - Han-Jia Ye; De-Chuan Zhan; Xue-Min Si; Yuan Jiang 001; Zhi-Hua Zhou (NIPS, 2016)

Deep Learning for Fixed Model Reuse. - Yang Yang 074; De-Chuan Zhan; Ying Fan; Yuan Jiang 001; Zhi-Hua Zhou (AAAI, 2017)

Instance Specific Discriminative Modal Pursuit: A Serialized Approach. - Yang Yang 074; De-Chuan Zhan; Ying Fan; Yuan Jiang 001 (ACML, 2017)

Obtaining High-Quality Label by Distinguishing between Easy and Hard Items in Crowdsourcing. - Wei Wang 028; Xiang-Yu Guo; Shao-Yuan Li; Yuan Jiang 001; Zhi-Hua Zhou (IJCAI, 2017)

Modal Consistency based Pre-Trained Multi-Model Reuse. - Yang Yang 074; De-Chuan Zhan; Xiang-Yu Guo; Yuan Jiang 001 (IJCAI, 2017)

Learning Mahalanobis Distance Metric: Considering Instance Disturbance Helps. - Han-Jia Ye; De-Chuan Zhan; Xue-Min Si; Yuan Jiang 001 (IJCAI, 2017)

Multimodal Linear Discriminant Analysis via Structural Sparsity. - Yu Zhang 006; Yuan Jiang 001 (IJCAI, 2017)

Multi-View Matrix Completion for Clustering with Side Information. - Peng Zhao 006; Yuan Jiang 001; Zhi-Hua Zhou (PAKDD (2), 2017)

Preference Relation-based Markov Random Fields for Recommender Systems. - Shaowu Liu; Gang Li 009; Truyen Tran 001; Yuan Jiang 001 (Mach. Learn., 2017)

Erratum to: Preference Relation-based Markov Random Fields for Recommender Systems. - Shaowu Liu; Gang Li 009; Truyen Tran 001; Yuan Jiang 001 (Mach. Learn., 2017)

Dual Set Multi-Label Learning. - Chong Liu 007; Peng Zhao 006; Sheng-Jun Huang; Yuan Jiang 001; Zhi-Hua Zhou (AAAI, 2018)

DMTMV: A Unified Learning Framework for Deep Multi-task Multi-view Learning. - Yi-Feng Wu; De-Chuan Zhan; Yuan Jiang 001 (ICBK, 2018)

Rectify Heterogeneous Models with Semantic Mapping. - Han-Jia Ye; De-Chuan Zhan; Yuan Jiang 001; Zhi-Hua Zhou (ICML, 2018)

Semi-Supervised Multi-Modal Learning with Incomplete Modalities. - Yang Yang 074; De-Chuan Zhan; Xiang-Rong Sheng; Yuan Jiang 001 (IJCAI, 2018)

Complex Object Classification: A Multi-Modal Multi-Instance Multi-Label Deep Network with Optimal Transport. - Yang Yang 074; Yi-Feng Wu; De-Chuan Zhan; Zhi-Bin Liu; Yuan Jiang 001 (KDD, 2018)

Multi-network User Identification via Graph-Aware Embedding. - Yang Yang 074; De-Chuan Zhan; Yi-Feng Wu; Yuan Jiang 001 (PAKDD (2), 2018)

Multi-label Crowdsourcing Learning with Incomplete Annotations. - Shao-Yuan Li; Yuan Jiang 001 (PRICAI (1), 2018)

Deep Multi-modal Learning with Cascade Consensus. - Yang Yang 074; Yi-Feng Wu; De-Chuan Zhan; Yuan Jiang 001 (PRICAI, 2018)

Multi-View Anomaly Detection: Neighborhood in Locality Matters. - Xiang-Rong Sheng; De-Chuan Zhan; Su Lu; Yuan Jiang 001 (AAAI, 2019)

Deep Robust Unsupervised Multi-Modal Network. - Yang Yang 074; Yi-Feng Wu; De-Chuan Zhan; Zhi-Bin Liu; Yuan Jiang 001 (AAAI, 2019)

Nearest Neighbor Ensembles: An Effective Method for Difficult Problems in Streaming Classification with Emerging New Classes. - Xin-Qiang Cai; Peng Zhao 006; Kai-Ming Ting; Xin Mu; Yuan Jiang 001 (ICDM, 2019)

Comprehensive Semi-Supervised Multi-Modal Learning. - Yang Yang 074; Ke-Tao Wang; De-Chuan Zhan; Hui Xiong 001; Yuan Jiang 001 (IJCAI, 2019)

Adaptive Deep Models for Incremental Learning: Considering Capacity Scalability and Sustainability. - Yang Yang 074; Da-Wei Zhou 001; De-Chuan Zhan; Hui Xiong 001; Yuan Jiang 001 (KDD, 2019)

Learning from Incomplete and Inaccurate Supervision. - Zhenyu Zhang; Peng Zhao 006; Yuan Jiang 001; Zhi-Hua Zhou (KDD, 2019)

Expert-Level Atari Imitation Learning from Demonstrations Only. - Xin-Qiang Cai; Yao-Xiang Ding 001; Yuan Jiang 001; Zhi-Hua Zhou (CoRR, 2019)

Fast generalization rates for distance metric learning. - Han-Jia Ye; De-Chuan Zhan; Yuan Jiang 001 (Mach. Learn., 2019)

What Makes Objects Similar: A Unified Multi-Metric Learning Approach. - Han-Jia Ye; De-Chuan Zhan; Yuan Jiang 001; Zhi-Hua Zhou (IEEE Trans. Pattern Anal. Mach. Intell., 2019)

Multi-Label Learning from Crowds. - Shao-Yuan Li; Yuan Jiang 001; Nitesh V. Chawla; Zhi-Hua Zhou (IEEE Trans. Knowl. Data Eng., 2019)

A Simple Approach for Non-stationary Linear Bandits. - Peng Zhao 006; Lijun Zhang 005; Yuan Jiang 001; Zhi-Hua Zhou (AISTATS, 2020)

Multi-Label Learning with Deep Forest. - Liang Yang; Xi-Zhu Wu; Yuan Jiang 001; Zhi-Hua Zhou (ECAI, 2020)

Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data. - Lan-Zhe Guo; Zhenyu Zhang; Yuan Jiang 001; Yufeng Li 008; Zhi-Hua Zhou (ICML, 2020)

Learning with Feature and Distribution Evolvable Streams. - Zhenyu Zhang; Peng Zhao 006; Yuan Jiang 001; Zhi-Hua Zhou (ICML, 2020)

Provably Robust Metric Learning. - Lu Wang 031; Xuanqing Liu; Jinfeng Yi; Yuan Jiang 001; Cho-Jui Hsieh (NeurIPS, 2020)

Soft Gradient Boosting Machine. - Ji Feng; Yi-Xuan Xu; Yuan Jiang 001; Zhi-Hua Zhou (CoRR, 2020)

Multi-label optimal margin distribution machine. - Zhi-Hao Tan; Peng Tan 002; Yuan Jiang 001; Zhi-Hua Zhou (Mach. Learn., 2020)

Spanning attack: reinforce black-box attacks with unlabeled data. - Lu Wang 031; Huan Zhang 001; Jinfeng Yi; Cho-Jui Hsieh; Yuan Jiang 001 (Mach. Learn., 2020)

Learning Multiple Local Metrics: Global Consideration Helps. - Han-Jia Ye; De-Chuan Zhan; Nan Li 019; Yuan Jiang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2020)

Federated Soft Gradient Boosting Machine for Streaming Data. - Ji Feng; Yi-Xuan Xu; Yong-Gang Wang; Yuan Jiang 001 (Federated Learning, 2020)

Isolation Graph Kernel. - Bi-Cun Xu; Kai Ming Ting; Yuan Jiang 001 (AAAI, 2021)

Imitation Learning from Pixel-Level Demonstrations by HashReward. - Xin-Qiang Cai; Yao-Xiang Ding 001; Yuan Jiang 001; Zhi-Hua Zhou (AAMAS, 2021)

Improving Deep Forest by Exploiting High-order Interactions. - Yi-He Chen; Shen-Huan Lyu; Yuan Jiang 001 (ICDM, 2021)

LIFE: Learning Individual Features for Multivariate Time Series Prediction with Missing Values. - Zhao-Yu Zhang; Shao-Qun Zhang; Yuan Jiang 001; Zhi-Hua Zhou (ICDM, 2021)

Abductive Learning with Ground Knowledge Base. - Le-Wen Cai; Wang-Zhou Dai; Yu-Xuan Huang; Yufeng Li 008; Stephen H. Muggleton; Yuan Jiang 001 (IJCAI, 2021)

Fast Abductive Learning by Similarity-based Consistency Optimization. - Yu-Xuan Huang; Wang-Zhou Dai; Le-Wen Cai; Stephen H. Muggleton; Yuan Jiang 001 (NeurIPS, 2021)

Reconstruction-based Anomaly Detection with Completely Random Forest. - Yi-Xuan Xu; Ming Pang; Ji Feng; Kai Ming Ting; Yuan Jiang 001; Zhi-Hua Zhou (SDM, 2021)

Seeing Differently, Acting Similarly: Imitation Learning with Heterogeneous Observations. - Xin-Qiang Cai; Yao-Xiang Ding 001; Zi-Xuan Chen; Yuan Jiang 001; Masashi Sugiyama; Zhi-Hua Zhou (CoRR, 2021)

Towards Theoretical Understanding of Flexible Transmitter Networks via Approximation and Local Minima. - Jin-Hui Wu; Shao-Qun Zhang; Yuan Jiang 001; Zhi-Hua Zhou (CoRR, 2021)

PU Active Learning for Recommender Systems. - Jia-Lue Chen; Jia-Jia Cai; Yuan Jiang 001; Sheng-Jun Huang (Neural Process. Lett., 2021)

Heterogeneous Few-Shot Model Rectification With Semantic Mapping. - Han-Jia Ye; De-Chuan Zhan; Yuan Jiang 001; Zhi-Hua Zhou (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

Semi-Supervised Multi-Modal Multi-Instance Multi-Label Deep Network with Optimal Transport. - Yang Yang 074; Zhao-Yang Fu; De-Chuan Zhan; Zhi-Bin Liu; Yuan Jiang 001 (IEEE Trans. Knowl. Data Eng., 2021)

Semi-Supervised Multi-Modal Clustering and Classification with Incomplete Modalities. - Yang Yang 074; De-Chuan Zhan; Yi-Feng Wu; Zhi-Bin Liu; Hui Xiong 001; Yuan Jiang 001 (IEEE Trans. Knowl. Data Eng., 2021)

Anomaly Guided Policy Learning from Imperfect Demonstrations. - Zi-Xuan Chen; Xin-Qiang Cai; Yuan Jiang 001; Zhi-Hua Zhou (AAMAS, 2022)

Adaptive Learning for Weakly Labeled Streams. - Zhen-Yu Zhang; Yu-Yang Qian 001; Yu-Jie Zhang; Yuan Jiang 001; Zhi-Hua Zhou (KDD, 2022)

Real-Valued Backpropagation is Unsuitable for Complex-Valued Neural Networks. - Zhi-Hao Tan; Yi Xie; Yuan Jiang 001; Zhi-Hua Zhou (NeurIPS, 2022)

Learning From Incomplete and Inaccurate Supervision. - Zhen-Yu Zhang; Peng Zhao 006; Yuan Jiang 001; Zhi-Hua Zhou (IEEE Trans. Knowl. Data Eng., 2022)

Enabling Knowledge Refinement upon New Concepts in Abductive Learning. - Yu-Xuan Huang; Wang-Zhou Dai; Yuan Jiang 001; Zhi-Hua Zhou (AAAI, 2023)

On the Consistency Rate of Decision Tree Learning Algorithms. - Qin-Cheng Zheng; Shen-Huan Lyu; Shao-Qun Zhang; Yuan Jiang 001; Zhi-Hua Zhou (AISTATS, 2023)

Adaptive Clustered Federated Learning with Representation Similarity. - Chiyu Cai; Wei Wang 028; Yuan Jiang 001 (DSAA, 2023)

Identifying Helpful Learnwares Without Examining the Whole Market. - Yi Xie; Zhi-Hao Tan; Yuan Jiang 001; Zhi-Hua Zhou (ECAI, 2023)

Seeing Differently, Acting Similarly: Heterogeneously Observable Imitation Learning. - Xin-Qiang Cai; Yao-Xiang Ding 001; Zi-Xuan Chen; Yuan Jiang 001; Masashi Sugiyama; Zhi-Hua Zhou (ICLR, 2023)

Enabling Abductive Learning to Exploit Knowledge Graph. - Yu-Xuan Huang; Zequn Sun; Guangyao Li; Xiaobin Tian; Wang-Zhou Dai; Wei Hu 007; Yuan Jiang 001; Zhi-Hua Zhou (IJCAI, 2023)

Handling Learnwares Developed from Heterogeneous Feature Spaces without Auxiliary Data. - Peng Tan 002; Zhi-Hao Tan; Yuan Jiang 001; Zhi-Hua Zhou (IJCAI, 2023)

A Multi-task Method for Immunofixation Electrophoresis Image Classification. - Yi Shi; Rui-Xiang Li; Wen-Qi Shao; Xin-Cen Duan; Han-Jia Ye; De-Chuan Zhan; Bai-Shen Pan; Bei-Li Wang; Wei Guo; Yuan Jiang 001 (MICCAI (6), 2023)

Complex-valued Neurons Can Learn More but Slower than Real-valued Neurons via Gradient Descent. - Jin-Hui Wu; Shao-Qun Zhang; Yuan Jiang 001; Zhi-Hua Zhou (NeurIPS, 2023)

On Transferring Expert Knowledge from Tabular Data to Images. - Jun-Peng Jiang; Han-Jia Ye; Leye Wang; Yang Yang 074; Yuan Jiang 001; De-Chuan Zhan (UniReps, 2023)

Interpreting Deep Forest through Feature Contribution and MDI Feature Importance. - Yi-Xiao He; Shen-Huan Lyu; Yuan Jiang 001 (CoRR, 2023)

Cost-Effective Incremental Deep Model: Matching Model Capacity With the Least Sampling. - Yang Yang 074; Da-Wei Zhou 001; De-Chuan Zhan; Hui Xiong 001; Yuan Jiang 001; Jian Yang 003 (IEEE Trans. Knowl. Data Eng., 2023)

Fully Decentralized Multiagent Communication via Causal Inference. - Han Wang; Yang Yu 001; Yuan Jiang 001 (IEEE Trans. Neural Networks Learn. Syst., 2023)

MEPSI: An MDL-Based Ensemble Pruning Approach with Structural Information. - Xiao-Dong Bi; Shao-Qun Zhang; Yuan Jiang 001 (AAAI, 2024)

Deciphering Raw Data in Neuro-Symbolic Learning with Provable Guarantees. - Lue Tao; Yu-Xuan Huang; Wang-Zhou Dai; Yuan Jiang 001 (AAAI, 2024)

Tabular Insights, Visual Impacts: Transferring Expertise from Tables to Images. - Jun-Peng Jiang; Han-Jia Ye; Leye Wang; Yang Yang 074; Yuan Jiang 001; De-Chuan Zhan (ICML, 2024)

Theoretical Exploration of Flexible Transmitter Model. - Jin-Hui Wu; Shao-Qun Zhang; Yuan Jiang 001; Zhi-Hua Zhou (IEEE Trans. Neural Networks Learn. Syst., 2024)

Towards enabling learnware to handle heterogeneous feature spaces. - Peng Tan 002; Zhi-Hao Tan; Yuan Jiang 001; Zhi-Hua Zhou (Mach. Learn., 2024)

ABLkit: a Python toolkit for abductive learning. - Yu-Xuan Huang; Wen-Chao Hu; En-Hao Gao; Yuan Jiang 001 (Frontiers Comput. Sci., 2024)

Efficient Rectification of Neuro-Symbolic Reasoning Inconsistencies by Abductive Reflection. - Wen-Chao Hu; Wang-Zhou Dai; Yuan Jiang 001; Zhi-Hua Zhou (AAAI, 2025)

Adapting to Generalized Online Label Shift by Invariant Representation Learning. - Yu-Yang Qian 001; Yi-Han Wang; Zhen-Yu Zhang; Yuan Jiang 001; Zhi-Hua Zhou (KDD (1), 2025)

Abductive multi-instance multi-label learning for periodontal disease classification with prior domain knowledge. - Zi-Yuan Wu; Wei Guo; Wei Zhou; Han-Jia Ye; Yuan Jiang 001; Houxuan Li; Zhi-Hua Zhou (Medical Image Anal., 2025)

Revisiting multi-dimensional classification from a dimension-wise perspective. - Yi Shi; Han-Jia Ye; Dongliang Man; Xiaoxu Han; De-Chuan Zhan; Yuan Jiang 001 (Frontiers Comput. Sci., 2025)

Curriculum Abductive Learning. - Wen-Chao Hu; Qi-Jie Li; Lin-Han Jia; Cunjing Ge; Yufeng Li 008; Yuan Jiang 001; Zhi-Hua Zhou (CoRR, 2025)

Theoretical Investigation on Inductive Bias of Isolation Forest. - Qin-Cheng Zheng; Shao-Qun Zhang; Shen-Huan Lyu; Yuan Jiang 001; Zhi-Hua Zhou (CoRR, 2025)