Multi-label Learning with Label Enhancement. - Ruifeng Shao; Ning Xu 009; Xin Geng 001 (ICDM, 2018)

Label Enhancement for Label Distribution Learning. - Ning Xu 009; An Tao; Xin Geng 001 (IJCAI, 2018)

Labeling Information Enhancement for Multi-label Learning with Low-Rank Subspace. - An Tao; Ning Xu 009; Xin Geng 001 (PRICAI (1), 2018)

Partial Label Learning via Label Enhancement. - Ning Xu 009; Jiaqi Lv; Xin Geng 001 (AAAI, 2019)

Weakly Supervised Multi-Label Learning via Label Enhancement. - Jiaqi Lv; Ning Xu 009; RenYi Zheng; Xin Geng 001 (IJCAI, 2019)

Partial Multi-Label Learning with Label Distribution. - Ning Xu 009; Yun-Peng Liu; Xin Geng 001 (AAAI, 2020)

Variational Label Enhancement. - Ning Xu 009; Jun Shu; Yun-Peng Liu; Xin Geng 001 (ICML, 2020)

Label Distribution for Learning with Noisy Labels. - Yun-Peng Liu; Ning Xu 009; Yu Zhang 004; Xin Geng 001 (IJCAI, 2020)

Video Summarization via Label Distributions Dual-Reward. - Yongbiao Gao; Ning Xu 009; Xin Geng 001 (IJCAI, 2021)

Instance-Dependent Partial Label Learning. - Ning Xu 009; Congyu Qiao; Xin Geng 001; Min-Ling Zhang (NeurIPS, 2021)

Compact learning for multi-label classification. - Jiaqi Lv; Tianran Wu; Cheng-Lun Peng; Yunpeng Liu; Ning Xu 009; Xin Geng 001 (Pattern Recognit., 2021)

Label Enhancement for Label Distribution Learning. - Ning Xu 009; Yun-Peng Liu; Xin Geng 001 (IEEE Trans. Knowl. Data Eng., 2021)

Learngene: From Open-World to Your Learning Task. - Qiu-Feng Wang 002; Xin Geng 001; Shuxia Lin; Shiyu Xia; Lei Qi 001; Ning Xu 009 (AAAI, 2022)

Fusion Label Enhancement for Multi-Label Learning. - Xingyu Zhao 002; Yuexuan An; Ning Xu 009; Xin Geng 001 (IJCAI, 2022)

Ambiguity-Induced Contrastive Learning for Instance-Dependent Partial Label Learning. - Shiyu Xia; Jiaqi Lv; Ning Xu 009; Xin Geng 001 (IJCAI, 2022)

One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement. - Ning Xu 009; Congyu Qiao; Jiaqi Lv; Xin Geng 001; Min-Ling Zhang (NeurIPS, 2022)

Decomposition-based Generation Process for Instance-Dependent Partial Label Learning. - Congyu Qiao; Ning Xu 009; Xin Geng 001 (CoRR, 2022)

Label distribution for multimodal machine learning. - Yi Ren; Ning Xu 009; Miaogen Ling; Xin Geng 001 (Frontiers Comput. Sci., 2022)

Feature-Induced Label Distribution for Learning with Noisy Labels. - Minxue Zhang; Ning Xu 009; Xin Geng 001 (Pattern Recognit. Lett., 2022)

Imbalanced Label Distribution Learning. - Xingyu Zhao 002; Yuexuan An; Ning Xu 009; Jing Wang 113; Xin Geng 001 (AAAI, 2023)

Towards Effective Visual Representations for Partial-Label Learning. - Shiyu Xia; Jiaqi Lv; Ning Xu 009; Gang Niu 001; Xin Geng 001 (CVPR, 2023)

Decompositional Generation Process for Instance-Dependent Partial Label Learning. - Congyu Qiao; Ning Xu 009; Xin Geng 001 (ICLR, 2023)

Progressive Purification for Instance-Dependent Partial Label Learning. - Ning Xu 009; Biao Liu; Jiaqi Lv; Congyu Qiao; Xin Geng 001 (ICML, 2023)

Revisiting Pseudo-Label for Single-Positive Multi-Label Learning. - Biao Liu; Ning Xu 009; Jiaqi Lv; Xin Geng 001 (ICML, 2023)

FREDIS: A Fusion Framework of Refinement and Disambiguation for Unreliable Partial Label Learning. - Congyu Qiao; Ning Xu 009; Jiaqi Lv; Yi Ren; Xin Geng 001 (ICML, 2023)

Unreliable Partial Label Learning with Recursive Separation. - Yu Shi; Ning Xu 009; Hua Yuan; Xin Geng 001 (IJCAI, 2023)

Learning From Biased Soft Labels. - Hua Yuan; Yu Shi; Ning Xu 009; Xu Yang 021; Xin Geng 001; Yong Rui (NeurIPS, 2023)

Learning From Biased Soft Labels. - Hua Yuan; Ning Xu 009; Yu Shi; Xin Geng 001; Yong Rui (CoRR, 2023)

Can Class-Priors Help Single-Positive Multi-Label Learning? - Biao Liu; Jie Wang; Ning Xu 009; Xin Geng 001 (CoRR, 2023)

Continuous label distribution learning. - Xingyu Zhao 002; Yuexuan An; Ning Xu 009; Xin Geng 001 (Pattern Recognit., 2023)

Fast Label Enhancement for Label Distribution Learning. - Ke Wang 047; Ning Xu 009; Miaogen Ling; Xin Geng 001 (IEEE Trans. Knowl. Data Eng., 2023)

Variational Label Enhancement. - Ning Xu 009; Jun Shu; RenYi Zheng; Xin Geng 001; Deyu Meng; Min-Ling Zhang (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Progressive Enhancement of Label Distributions for Partial Multilabel Learning. - Ning Xu 009; Yun-Peng Liu; Yan Zhang; Xin Geng 001 (IEEE Trans. Neural Networks Learn. Syst., 2023)

Multi-View Partial Multi-Label Learning via Graph-Fusion-Based Label Enhancement. - Ning Xu 009; Yong-Di Wu; Congyu Qiao; Yi Ren; Minxue Zhang; Xin Geng 001 (IEEE Trans. Knowl. Data Eng., 2023)

Trusted-Data-Guided Label Enhancement on Noisy Labels. - Ning Xu 009; Jia-Yu Li; Yun-Peng Liu; Xin Geng 001 (IEEE Trans. Neural Networks Learn. Syst., 2023)

Variational Label-Correlation Enhancement for Congestion Prediction. - Biao Liu; Congyu Qiao; Ning Xu 009; Xin Geng 001; Ziran Zhu; Jun Yang 006 (ASPDAC, 2024)

Aligned Objective for Soft-Pseudo-Label Generation in Supervised Learning. - Ning Xu 009; Yihao Hu 004; Congyu Qiao; Xin Geng 001 (ICML, 2024)

Correlation-Induced Label Prior for Semi-Supervised Multi-Label Learning. - Biao Liu; Ning Xu 009; Xiangyu Fang; Xin Geng 001 (ICML, 2024)

Learning with Partial-Label and Unlabeled Data: A Uniform Treatment for Supervision Redundancy and Insufficiency. - Yangfan Liu; Jiaqi Lv; Xin Geng 001; Ning Xu 009 (ICML, 2024)

ULAREF: A Unified Label Refinement Framework for Learning with Inaccurate Supervision. - Congyu Qiao; Ning Xu 009; Yihao Hu 004; Xin Geng 001 (ICML, 2024)

What Makes Partial-Label Learning Algorithms Effective? - Jiaqi Lv; Yangfan Liu; Shiyu Xia; Ning Xu 009; Miao Xu 001; Gang Niu 001; Min-Ling Zhang; Masashi Sugiyama; Xin Geng 001 (NeurIPS, 2024)

ChipExpert: The Open-Source Integrated-Circuit-Design-Specific Large Language Model. - Ning Xu 009; Zhaoyang Zhang; Lei Qi 001; Wensuo Wang; Chao Zhang; Zihao Ren; Huaiyuan Zhang; Xin Cheng; Yanqi Zhang; Zhichao Liu; Qingwen Wei; Shiyang Wu; et al. (CoRR, 2024)

Progressively Selective Label Enhancement for Language Model Alignment. - Biao Liu; Ning Xu 009; Xin Geng 001 (CoRR, 2024)

Reduction-based Pseudo-label Generation for Instance-dependent Partial Label Learning. - Congyu Qiao; Ning Xu 009; Yihao Hu 004; Xin Geng 001 (CoRR, 2024)

On the Robustness of Average Losses for Partial-Label Learning. - Jiaqi Lv; Biao Liu; Lei Feng 006; Ning Xu 009; Miao Xu 001; Bo An 001; Gang Niu 001; Xin Geng 001; Masashi Sugiyama (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Variational Continuous Label Distribution Learning for Multi-Label Text Classification. - Xingyu Zhao 002; Yuexuan An; Ning Xu 009; Xin Geng 001 (IEEE Trans. Knowl. Data Eng., 2024)

LAMPlace: Legalization-Aided Reinforcement Learning-Based Macro Placement for Mixed-Size Designs With Preplaced Blocks. - Hao Gu; Jian Gu; Keyu Peng; Ziran Zhu; Ning Xu 009; Xin Geng 001; Jun Yang 006 (IEEE Trans. Circuits Syst. II Express Briefs, 2024)

Variational Label Enhancement for Instance-Dependent Partial Label Learning. - Ning Xu 009; Congyu Qiao; Yuchen Zhao; Xin Geng 001; Min-Ling Zhang (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Selective Label Enhancement Learning for Test-Time Adaptation. - Yihao Hu 004; Congyu Qiao; Xin Geng 001; Ning Xu 009 (ICLR, 2025)

Leveraging Bilateral Correlations for Multi-Label Few-Shot Learning. - Yuexuan An; Hui Xue 002; Xingyu Zhao 002; Ning Xu 009; Pengfei Fang; Xin Geng 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)

MMCircuitEval: A Comprehensive Multimodal Circuit-Focused Benchmark for Evaluating LLMs. - Chenchen Zhao; Zhengyuan Shi; Xiangyu Wen; Chengjie Liu; Yi Liu; Yunhao Zhou; Yuxiang Zhao; Hefei Feng; Yinan Zhu; Gwok-Waa Wan; Xin Cheng; Weiyu Chen; et al. (CoRR, 2025)

Interactive Fusion Label Enhancement for Multi-Label Learning. - Xingyu Zhao 002; Yuexuan An; Ning Xu 009; Lei Qi 001; Xin Geng 001 (ACM Trans. Knowl. Discov. Data, 2025)