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J. Chen, Y. Qiao, N. Xu, X. Lv, Z. Kou, X. Sheng. LoGoSeg: Integrating Local and Global Features for Open-Vocabulary Semantic Segmentation. In: Proceedings of the 40th AAAI Conference on Artificial Intelligence (AAAI 2026), Singapore, 2026, in press. (CCF-A)
B. Liu, N. Xu*, J. Wang, X. Geng. Can Class-Priors Help Single-Positive Multi-Label Learning? In: Advances in Neural Information Processing Systems 38 (NeurIPS 2025), San Diego, USA, 2025, in press. (CCF-A)
C. Qiao, N. Xu*, Y. Hu, X. Geng. Reduction-based Pseudo-label Generation for Instance-dependent Partial Label Learning. In: Advances in Neural Information Processing Systems 38 (NeurIPS 2025), San Diego, USA, 2025, in press. (CCF-A)
T. Wu, S. Zhu, J. Wang, N. Xu*, G. Qi, H. Wang. Uncertain Knowledge Graph Completion via Semi-Supervised Confidence Distribution Learning. In: Advances in Neural Information Processing Systems 38 (NeurIPS 2025), San Diego, USA, 2025, in press. (CCF-A, Spotlight)
B. Liu, N. Xu*, X. Geng. Progressively Label Enhancement for Large Language Model Alignment. In: Proceedings of the 42nd International Conference on Machine Learning (ICML 2025), Vancouver, Canada, 2025, in press. (CCF-A)
Y. Hu, C. Qiao, X. Geng, N. Xu*. Selective Label Enhancement Learning for Test-Time Adaptation. In: Proceedings of the 13th International Conference on Learning Representations (ICLR 2025), Singapore, 2025.
J. Wang, N. Xu*, X. Geng. VADIS: Investigating Inter-View Representation Biases for Multi-View Partial Multi-Label Learning. In: Proceedings of the 41st Conference on Uncertainty in Artificial Intelligence (UAI 2025), Rio de Janeiro, Brazil, 2025, in press. (CCF-B)
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Y. An, H. Xue, X. Zhao, N. Xu, P. Fang, X. Geng. Leveraging Bilateral Correlations for Multi-Label Few-Shot Learning. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2025, 36(4): 6816-6828. (CCF-B)
N. Xu, C. Qiao, Y. Zhao, X. Geng, M.-L. Zhang. Variational Label Enhancement for Instance-Dependent Partial Label Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2024, 46(12): 11298-11313. (CCF-A)
J. Lv, B. Liu, L. Feng, N. Xu, M. Xu, B. An, G. Niu, X. Geng, M. Sugiyama. On the Robustness of Average Losses for Partial-Label Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2024, 46(5): 2569-2583. (CCF-A)
B. Liu, C. Qiao, N. Xu*, X. Geng, Z. Zhu, J. Yang. Variational Label-Correlation Enhancement for Congestion Prediction. In: Proceedings of the 29th Asia and South Pacific Design Automation Conference (ASPDAC 2024), Incheon, South Korea, 2024, 466-471. (CCF-C)
Y. Liu, J. Lv, X. Geng, N. Xu*. Learning with Partial-Label and Unlabeled Data: A Uniform Treatment for Supervision Redundancy and Insufficiency. In: Proceedings of the 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria, 2024, 31614-31628. (CCF-A)
B. Liu, N. Xu*, X. Fang, X. Geng. Correlation-induced label prior for semi-supervised multi-label learning. In: Proceedings of the 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria, 2024. (CCF-A)
C. Qiao, N. Xu*, Y. Hu, X. Geng. ULAREF: A unified label refinement framework for learning with inaccurate supervision. In: Proceedings of the 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria, 2024. (CCF-A)
N. Xu, Y. Hu, C. Qiao, X. Geng. Aligned Objective for Soft-Pseudo-Label Generation in Supervised Learning. In: Proceedings of the 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria, 2024, 55033-55047. (CCF-A)
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H. Gu, J. Gu, K. Peng, Z. Zhu, N. Xu, X. Geng, J. Yang. LAMPlace: Legalization-Aided Reinforcement Learning-Based Macro Placement for Mixed-Size Designs With Preplaced Blocks. IEEE Transactions on Circuits and Systems II (IEEE TCS-II), 2024, 71(8): 3770-3774.
X. Zhao, Y. An, N. Xu, X. Geng. Variational Continuous Label Distribution Learning for Multi-Label Text Classification. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2024, 36(6): 2716-2729. (CCF-A)
B. Liu, N. Xu*, J. Lv, X. Geng. Revisiting Pseudo-Label for Single-Positive Multi-Label Learning. In: Proceedings of the 40th International Conference on Machine Learning (ICML 2023), Honolulu, Hawaii, USA, 2023, 22249-22265. (CCF-A)
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N. Xu, B. Liu, J. Lv, C. Qiao, X. Geng. Progressive Purification for Instance-Dependent Partial Label Learning. In: Proceedings of the 40th International Conference on Machine Learning (ICML 2023), Honolulu, Hawaii, USA, 2023, 38551-38565. (CCF-A)
C. Qiao, N. Xu*, X. Geng. Decompositional Generation Process for Instance-Dependent Partial Label Learning. In: Proceedings of the 11th International Conference on Learning Representations (ICLR 2023), Kigali, Rwanda, 2023. (Spotlight)
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X. Zhao, Y. An, N. Xu, X. Geng. Continuous label distribution learning. Pattern Recognition (PR), 2023, 133: 109056. (CCF-B)
K. Wang, N. Xu, M. Ling, X. Geng. Fast Label Enhancement for Label Distribution Learning. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2023, 35(2): 1502-1514. (CCF-A)
N. Xu, Y.-P. Liu, Y. Zhang, X. Geng. Progressive Enhancement of Label Distributions for Partial Multilabel Learning. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2023, 34(8): 4856-4867. (CCF-B)
N. Xu, J.-Y. Li, Y.-P. Liu, X. Geng. Trusted-Data-Guided Label Enhancement on Noisy Labels. IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2023, 34(12): 9940-9951. (CCF-B)
X. Zhao, Y. An, N. Xu, J. Wang, X. Geng. Imbalanced Label Distribution Learning. In: Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI 2023), Washington, DC, USA, 2023, 11336-11344. (CCF-A)
S. Xia, J. Lv, N. Xu, G. Niu, X. Geng. Towards Effective Visual Representations for Partial-Label Learning. In: Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2023), Vancouver, Canada, 2023, 15589-15598. (CCF-A)
Y. Shi, N. Xu*, H. Yuan, X. Geng. Unreliable Partial Label Learning with Recursive Separation. In: Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI 2023), Macao, China, 2023, 4208-4216. (CCF-A)
H. Yuan, Y. Shi, N. Xu, X. Yang, X. Geng, Y. Rui. Learning from biased soft labels. In: Advances in Neural Information Processing Systems 36 (NeurIPS 2023), New Orleans, USA, 2023, 59566-59584. (CCF-A)
N. Xu, C. Qiao, J. Lv, X. Geng, M.-L. Zhang. One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement. In: Advances in Neural Information Processing Systems 35 (NeurIPS 2022), New Orleans, USA, 2022, 21765-21776. (CCF-A, Oral)
Y. Ren, N. Xu, M. Ling, X. Geng. Label distribution for multimodal machine learning. Frontiers of Computer Science (FCS), 2022, 16(1): 161306. (CCF-B)
M. Zhang, N. Xu*, X. Geng. Feature-Induced Label Distribution for Learning with Noisy Labels. Pattern Recognition Letters (PRL), 2022, 155: 107-113. (CCF-C)
Q.-F. Wang, X. Geng, S. Lin, S. Xia, L. Qi, N. Xu. Learngene: From Open-World to Your Learning Task. In: Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI 2022), Virtual, 2022, 8557-8565. (CCF-A)
S. Xia, J. Lv, N. Xu, X. Geng. Ambiguity-Induced Contrastive Learning for Instance-Dependent Partial Label Learning. In: Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI 2022), Vienna, Austria, 2022, 3615-3621. (CCF-A)
X. Zhao, Y. An, N. Xu, X. Geng. Fusion Label Enhancement for Multi-Label Learning. In: Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI 2022), Vienna, Austria, 2022, 3773-3779. (CCF-A)
N. Xu, Y.-P. Liu, and X. Geng. Label Enhancement for Label Distribution Learning. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2021, 33(4): 1632-1643. (CCF-A)
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Y. Gao, N. Xu, X. Geng. Video Summarization via Label Distributions Dual-Reward. In: Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI 2021), Montreal, Canada (Virtual), 2021, 2403-2409. (CCF-A)
N. Xu, J. Shu, Y.-P. Liu, X. Geng. Variational Label Enhancement. In: Proceedings of the 37th International Conference on Machine Learning (ICML 2020), Vienna, Austria (Virtual), 2020, 10597-10606. (CCF-A)
N. Xu, Y.-P. Liu, X. Geng. Partial Multi-Label Learning with Label Distribution. In: Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI 2020), New York, NY, USA, 2020, 6510-6517. (CCF-A)
Y.-P. Liu, N. Xu, Y. Zhang, X. Geng. Label Distribution for Learning with Noisy Labels. In: Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020), Yokohama, Japan (Virtual), 2020, 2568-2574. (CCF-A)
N. Xu, J. Lv, X. Geng. Partial Label Learning via Label Enhancement. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI 2019), Honolulu, Hawaii, USA, 2019, 5557-5564. (CCF-A)
J. Lv, N. Xu, R.-Y. Zheng, X. Geng. Weakly Supervised Multi-Label Learning via Label Enhancement. In: Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), Macao, China, 2019, 3101-3107. (CCF-A)
N. Xu, A. Tao and X. Geng. Label Enhancement for Label Distribution Learning. In: Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI 2018), Stockholm, Sweden, 2018, 2926-2932. (CCF-A)
R. Shao, N. Xu, X. Geng. Multi-label Learning with Label Enhancement. In: Proceedings of the 18th IEEE International Conference on Data Mining (ICDM 2018), Singapore, 2018, 437-446. (CCF-B)
A. Tao, N. Xu, X. Geng. Labeling Information Enhancement for Multi-label Learning with Low-Rank Subspace. In: Proceedings of the 15th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2018), Nanjing, China, 2018, 671-683. (CCF-C)