Yuheng Jia
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Papers are listed below, in descending order by year of submission before they are published, or year of publication.

Generally, the codes of all the papers will be available.

The works that I personally like the most

Preprint

  • Towards Better IncomLDL: We Are Unaware of Hidden Labels in Advance

  • Similarity and Dissimilarity Guided Co-association Matrix Construction for Ensemble Clustering

  • DPtSTrip: Adversarially Robust Learning with Distance-Aware Point-to-Set Triplet Loss

  • Large Model Guided Semantic Segment Anything for Underwater Consumer Electronics

  • Inaccurate Label Distribution Learning with Dependency Noise

  • RankMatch: A Novel Approach to Semi-Supervised Label Distribution Learning Leveraging Inter-label Correlations

  • Adaptive Graph Feedback Clustering Network

Journal Papers

Conference Papers

  • [MLMC] Fuchao Yang, Yongqiang Dong, Yuheng Jia, Partial Label Learning Tailored Graph Construction, The 2025 IEEE International Symposium on Machine Learning and Media Computing.

  • [ACL] Jinghan He, Kuan Zhu, Haiyun Guo, Junfeng Fang, Zhenglin Hua, Yuheng Jia, Ming Tang, Tat-Seng Chua, Jinqiao Wang, Cracking the Code of Hallucination in LVLMs with Vision-aware Head Divergence, The 63rd Annual Meeting of the Association for Computational Linguistics.

  • [ICML] Zhixin Li, Yuheng Jia, Hui Liu, Junhui Hou, Learning from Sample Stability for Deep Clustering,, International Conference on Machine Learning, 13th-19th July, Vancouver, 2025.

  • [ICML] Xu Zhang, Haoye Qiu, Weixuan Liang, Hui LIU, Junhui Hou, Yuheng Jia, Generalization Performance of Ensemble Clustering: From Theory to Algorithm,, International Conference on Machine Learning, 13th-19th July, Vancouver, 2025.

  • [ICML] Yaxin Hou, Yuheng Jia, A Square Peg in a Square Hole: Meta-Expert for Long-Tailed Semi-Supervised Learning, International Conference on Machine Learning, 13th-19th July, Vancouver, 2025.

  • [ICML] Jiawei Tang, Yuheng Jia, Concentration Distribution Learning from Label Distributions , International Conference on Machine Learning, 13th-19th July, Vancouver, 2025.

  • [IJCAI] Yutong Xie, Fuchao Yang, Yuheng Jia, Partial Label Clustering, International Joint Conference on Artificial Intelligence (IJCAI), Montreal, 16th – 22nd August, 2025.

  • [IJCAI] Zhiqiang kou, Si Qin, Hailin Wang, Ming-Kun Xie, Jing Wang, Shuo Chen, Yuheng Jia, Tongliang Liu, Mas, ashi Sugiyama, Xin Geng, Label Distribution Learning with Biased Annotations Assisted by Multi-Label Learning, International Joint Conference on Artificial Intelligence (IJCAI), Montreal, 16th – 22nd August, 2025.

  • [ICLR] Yuheng Jia, Jianhong Cheng, Hui LIU, Junhui Hou, Towards Calibrated Deep Clustering Network, International Conference on Learning Representations, Singapore, 2025-04-24~2025-04-28. code

  • [ICLR] Zhixin Li, Yuheng Jia, ConMix: Contrastive Mixup at Representation Level for Long-tailed Deep Clustering, International Conference on Learning Representations, Singapore, 2025-04-24~2025-04-28.

  • [ICLR] Xiaorui Peng, Yuheng Jia, Fuchao Yang, Ran Wang, Min-Ling Zhang, Noise Separation guided Candidate Label Reconstruction for Noisy Partial Label Learning, International Conference on Learning Representations, Singapore, 2025-04-24~2025-04-28. code

  • [ICLR] Yuhang Li, Zhuying Li, Yuheng Jia, Complementary Label Learning with Positive Label Guessing and Negative Label Enhancement,, International Conference on Learning Representations, Singapore, 2025-04-24~2025-04-28.

  • [AAAI] Zhuoming Li, Yuheng Jia, Mi Yu, Zicong Miao, Calibrated Disambiguation for Partial Multi-Label Learning, AAAI Conference on Artificial Intelligence, Philadelphia, Pennsylvania, USA, 2025-02-25~2025-03-04.

  • [KDD] Fuchao Yang, Jianhong Cheng, Hui LIU, Yongqiang Dong, Yuheng Jia, Junhui Hou, Mixed Blessing: Class-Wise Embedding guided Instance-Dependent Partial Label Learning, ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Toronto, ON, Canada, 2025-08-03~2025-08-07.

  • [SMC] Ran Wang, Simeng Zeng, Wenhui Wu, Yuheng Jia, Wing Yin Ng, Xizhao Wang, On the Adversarial Robustness of Hierarchical Classification, 2024.

  • [KDD] Fuchao Yang, Yuheng Jia, Hui LIU, Yongqiang Dong, Junhui Hou, Noisy Label Removal for Partial Multi-Label Learning, ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Barcelona, Spain, 2024-08-25~2024-08-29. code

  • [KDD] Jiahao Jiang, Yuheng Jia, Hui LIU, Junhui Hou, FairMatch: Promoting Partial Label Learning by Unlabeled Samples , ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Barcelona, Spain, 2024-08-25~2024-08-29. code

  • [IJCAI] Zhiqiang Kou, Jing Wang, Jiawei Tang, Yuheng Jia, Boyu Shi, Xin Geng, Exploiting Multi-Label Correlation in Label Distribution Learning Exploiting Multi-Label Correlation in Label Distribution Learning, International Joint Conference on Artificial Intelligence (IJCAI), Jeju Island, South Korea, 2024-08-03~2024-08-09.

  • [IJCAI] Yuheng Jia, Jiawei Tang, Jiahao Jiang, Label Distribution Learning from Logical Label , International Joint Conference on Artificial Intelligence, International Joint Conference on Artificial Intelligence (IJCAI), Jeju Island, South Korea, 2024-08-03~2024-08-09. code

  • [AAAI] Yuheng Jia, Xiaorui Peng, Ran Wang, Ming-Ling Zhang, Long-tailed Partial Label Learning by Head Classifier and Tail Classifier Cooperation, AAAI Conference on Artificial Intelligence, Vancouver, British Columbia, Canada, 2024-02-20~2024-02-27. code

  • [TRB] Yang He, Chengchuan An, Yuheng Jia, Jiaochao Liu, Efficient and Robust Freeway Traffic State Estimation under Oblique Grid using Vehicle Trajectory Data, Transportation Research Board Annual Meeting, 2024.

  • [TRB] Liyang Hu, Yuheng Jia, Weijie Chen, Dongjie Liu, Jianke Cheng, Zhirui Ye, When Missingness Meets Anomalies: A Tailored Low-rank Tensor Completion Approach for Traffic Data Recovery, Transportation Research Board Annual Meeting, 2024.

  • [NeurIPS] Yuheng Jia, Fuchao Yang, Yongqiang Dong, Partial Label Learning with Dissimilarity Propagation guided Candidate Label Shrinkage, Thirty-seventh Conference on Neural Information Processing Systems, New Orleans, Louisiana, USA, 2023-11-28~2023-12-09. code

  • [KDD] Yuheng Jia, Chongjie Si, Min-Ling Zhang, Complementary Classifier Induced Partial Label Learning, Twenty-ninth ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Long Beach, CA, USA, 2023-08-06~2023-08-10, pp. 974–983. code

  • [KDD] Yuheng Jia, Jiahao Jiang, Yongheng Wang, Semantic Dissimilarity Guided Locality Preserving Projections for Partial Label Dimensionality Reduction, Twenty-ninth ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Long Beach, CA, USA, 2023-08-06~2023-08-10, pp. 964–973. code

  • [ICMLC] Ran Wang, Jingyu Xiang, Haopeng Ke, Yuheng Jia, Debby D. Wang, Improving the Adversarial Robustness of Deep Neural Networks via Efficient Two Stage Training, International Conference on Machine Learning and Cybernetics, Adelaide, Australia, 2023-07-09~2023-07-11. code

  • [ACM MM] Zhihao Peng, Hui Liu, Yuheng Jia, Junhui Hou, Attention-driven graph clustering network, ACM International Conference on Multimedia, Virtual Conference, 2021-10-20~2021-10-24, pp. 935–943. code

  • [AAAI] Yuheng Jia, Hui Liu, Junhui Hou, Qingfu Zhang, Clustering ensemble meets low-rank tensor approximation, AAAI Conference on Artificial Intelligence, Virtual Conference, 2021-02-02~2021-02-09. code

  • [ACM MM] Hui Liu, Yuheng Jia, Junhui Hou, Qingfu Zhang, Imbalance-aware pairwise constraint propagation, ACM International Conference on Multimedia, Nice France, 2019-10-21~2019-10-25, pp. 1605–1613.

  • [ICME] Yuheng Jia, Sam Kwong, Junhui Hou, Wenhui Wu, Convex Constrained Clustering with Graph-Laplacian PCA, IEEE International Conference on Multimedia and Expo, San Diego, USA, 2018-07-23~2018-07-27, pp. 1-6.

  • [FUZZ-IEEE] Ran Wang, Sam Kwong, Yuheng Jia, Zhiqi Huang, Lang Wu, Mutual Information Based K-Labelsets Ensemble for Multi-Label Classification, IEEE International Conference on Fuzzy Systems, Rio de Janeiro, Brazil, 2018-07-08~2018-07-13.

  • [IntelliSys] Yuheng Jia, Sam Kwong, Wenhui Wu, Wei Gao, Ran Wang, Generalized Relevance Vector Machine, Intelligent Systems Conference, London, UK, 2017-09-07~2017-09-08, pp. 638-645.

  • [GECCO] Mengyuan Wu, Sam Kwong, Yuheng Jia, Ke Li, Qingfu Zhang, Adaptive Weights Generation for Decomposition-based Multi-objective Optimization Using Gaussian Process Regression, Genetic and Evolutionary Computation Conference, Berlin Germany, 2017-07-15~2017-07-19.

  • [ICMLC] Wei Gao, Sam Kwong, Yu Zhou, Yuheng Jia, Jia Zhang, Wenhui Wu, Multiscale Phase Congruency Analysis for Image Edge Visual Saliency Detection, International Conference on Machine Learning and Cybernetics, Jeju Island, South Korea, 2016-07-10~2016-07-13.