A driving behavior detection system based on a smartphone's built-in sensor. - Yantao Li 001; Fengtao Xue; Lei Feng 006; Zehui Qu (Int. J. Commun. Syst., 2017)

Estimating Latent Relative Labeling Importances for Multi-label Learning. - Shuo He 001; Lei Feng 006; Li Li 006 (ICDM, 2018)

Leveraging Latent Label Distributions for Partial Label Learning. - Lei Feng 006; Bo An 001 (IJCAI, 2018)

Partial Label Learning with Self-Guided Retraining. - Lei Feng 006; Bo An 001 (AAAI, 2019)

Collaboration Based Multi-Label Learning. - Lei Feng 006; Bo An 001; Shuo He 001 (AAAI, 2019)

Fast Top-N Personalized Recommendation on Item Graph. - Zhuoyi Lin; Lei Feng 006; Chee-Keong Kwoh 001; Chi Xu (IEEE BigData, 2019)

Partial Label Learning by Semantic Difference Maximization. - Lei Feng 006; Bo An 001 (IJCAI, 2019)

EXACT: Attributed Entity Extraction By Annotating Texts. - Ke Chen 005; Lei Feng 006; Qingkuang Chen; Gang Chen 001; Lidan Shou (SIGIR, 2019)

Learning from Multiple Complementary Labels. - Lei Feng 006; Bo An 001 (CoRR, 2019)

Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization. - Hongxin Wei; Lei Feng 006; Xiangyu Chen; Bo An 001 (CVPR, 2020)

Learning with Multiple Complementary Labels. - Lei Feng 006; Takuo Kaneko; Bo Han 003; Gang Niu 001; Bo An 001; Masashi Sugiyama (ICML, 2020)

Progressive Identification of True Labels for Partial-Label Learning. - Jiaqi Lv; Miao Xu 001; Lei Feng 006; Gang Niu 001; Xin Geng 001; Masashi Sugiyama (ICML, 2020)

Can Cross Entropy Loss Be Robust to Label Noise? - Lei Feng 006; Senlin Shu; Zhuoyi Lin; Fengmao Lv; Li Li 006; Bo An 001 (IJCAI, 2020)

Discovering Latent Class Labels for Multi-Label Learning. - Jun Huang 003; Linchuan Xu; Jing Wang 023; Lei Feng 006; Kenji Yamanishi (IJCAI, 2020)

Provably Consistent Partial-Label Learning. - Lei Feng 006; Jiaqi Lv; Bo Han 003; Miao Xu 001; Gang Niu 001; Xin Geng 001; Bo An 001; Masashi Sugiyama (NeurIPS, 2020)

Learning Cross-domain Semantic-Visual Relation for Transductive Zero-Shot Learning. - Jianyang Zhang; Fengmao Lv; Guowu Yang; Lei Feng 006; Yufeng Yu; Lixin Duan (CoRR, 2020)

Incorporating Multiple Cluster Centers for Multi-Label Learning. - Senlin Shu; Fengmao Lv; Lei Feng 006; Jun Huang 003; Shuo He 001; Jun He 012; Li Li 006 (CoRR, 2020)

COMET: Convolutional Dimension Interaction for Deep Matrix Factorization. - Zhuoyi Lin; Lei Feng 006; Xingzhi Guo; Rui Yin 002; Chee Keong Kwoh 001; Chi Xu (CoRR, 2020)

MetaInfoNet: Learning Task-Guided Information for Sample Reweighting. - Hongxin Wei; Lei Feng 006; Rundong Wang; Bo An 001 (CoRR, 2020)

Attention is not Enough: Mitigating the Distribution Discrepancy in Asynchronous Multimodal Sequence Fusion. - Tao Liang; Guosheng Lin; Lei Feng 006; Yan Zhang 036; Fengmao Lv (ICCV, 2021)

Learning from Similarity-Confidence Data. - Yuzhou Cao; Lei Feng 006; Yitian Xu; Bo An 001; Gang Niu 001; Masashi Sugiyama (ICML, 2021)

Pointwise Binary Classification with Pairwise Confidence Comparisons. - Lei Feng 006; Senlin Shu; Nan Lu; Bo Han 003; Miao Xu 001; Gang Niu 001; Bo An 001; Masashi Sugiyama (ICML, 2021)

Learning from Complementary Labels via Partial-Output Consistency Regularization. - Deng-Bao Wang; Lei Feng 006; Min-Ling Zhang (IJCAI, 2021)

Multiple-Instance Learning from Similar and Dissimilar Bags. - Lei Feng 006; Senlin Shu; Yuzhou Cao; Lue Tao; Hongxin Wei; Tao Xiang 001; Bo An 001; Gang Niu 001 (KDD, 2021)

Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training. - Lue Tao; Lei Feng 006; Jinfeng Yi; Sheng-Jun Huang; Songcan Chen (NeurIPS, 2021)

Rethinking Calibration of Deep Neural Networks: Do Not Be Afraid of Overconfidence. - Deng-Bao Wang; Lei Feng 006; Min-Ling Zhang (NeurIPS, 2021)

Provable Defense Against Delusive Poisoning. - Lue Tao; Lei Feng 006; Jinfeng Yi; Sheng-Jun Huang; Songcan Chen (CoRR, 2021)

On the Robustness of Average Losses for Partial-Label Learning. - Jiaqi Lv; Lei Feng 006; Miao Xu 001; Bo An 001; Gang Niu 001; Xin Geng 001; Masashi Sugiyama (CoRR, 2021)

Multi-Class Classification from Single-Class Data with Confidences. - Yuzhou Cao; Lei Feng 006; Senlin Shu; Yitian Xu; Bo An 001; Gang Niu 001; Masashi Sugiyama (CoRR, 2021)

Embedding-Augmented Generalized Matrix Factorization for Recommendation With Implicit Feedback. - Lei Feng 006; Hongxin Wei; Qingyu Guo; Zhuoyi Lin; Bo An 001 (IEEE Intell. Syst., 2021)

GLIMG: Global and local item graphs for top-N recommender systems. - Zhuoyi Lin; Lei Feng 006; Rui Yin 002; Chi Xu; Chee Keong Kwoh 001 (Inf. Sci., 2021)

Partial multi-label learning with mutual teaching. - Yan Yan 025; Shining Li; Lei Feng 006 (Knowl. Based Syst., 2021)

Advanced topics in weakly supervised learning - Lei Feng 006 (2021)

With False Friends Like These, Who Can Notice Mistakes? - Lue Tao; Lei Feng 006; Jinfeng Yi; Songcan Chen (AAAI, 2022)

GearNet: Stepwise Dual Learning for Weakly Supervised Domain Adaptation. - Renchunzi Xie; Hongxin Wei; Lei Feng 006; Bo An 001 (AAAI, 2022)

Who Is Your Right Mixup Partner in Positive and Unlabeled Learning. - Changchun Li; Ximing Li 002; Lei Feng 006; Jihong Ouyang (ICLR, 2022)

PiCO: Contrastive Label Disambiguation for Partial Label Learning. - Haobo Wang 001; Ruixuan Xiao; Yixuan Li 001; Lei Feng 006; Gang Niu 001; Gang Chen 001; Junbo Zhao 002 (ICLR, 2022)

Exploiting Class Activation Value for Partial-Label Learning. - Fei Zhang; Lei Feng 006; Bo Han 003; Tongliang Liu; Gang Niu 001; Tao Qin; Masashi Sugiyama (ICLR, 2022)

Open-Sampling: Exploring Out-of-Distribution data for Re-balancing Long-tailed datasets. - Hongxin Wei; Lue Tao; Renchunzi Xie; Lei Feng 006; Bo An 001 (ICML, 2022)

Mitigating Neural Network Overconfidence with Logit Normalization. - Hongxin Wei; Renchunzi Xie; Hao Cheng 014; Lei Feng 006; Bo An 001; Yixuan Li 001 (ICML, 2022)

Partial Label Learning with Semantic Label Representations. - Shuo He 001; Lei Feng 006; Fengmao Lv; Wen Li 001; Guowu Yang (KDD, 2022)

Generalizing Consistent Multi-Class Classification with Rejection to be Compatible with Arbitrary Losses. - Yuzhou Cao; Tianchi Cai; Lei Feng 006; Lihong Gu; Jinjie Gu; Bo An 001; Gang Niu 001; Masashi Sugiyama (NeurIPS, 2022)

Can Adversarial Training Be Manipulated By Non-Robust Features? - Lue Tao; Lei Feng 006; Hongxin Wei; Jinfeng Yi; Sheng-Jun Huang; Songcan Chen (NeurIPS, 2022)

SoLar: Sinkhorn Label Refinery for Imbalanced Partial-Label Learning. - Haobo Wang 001; Mingxuan Xia; Yixuan Li 001; Yuren Mao; Lei Feng 006; Gang Chen 001; Junbo Zhao 002 (NeurIPS, 2022)

ProMix: Combating Label Noise via Maximizing Clean Sample Utility. - Haobo Wang 001; Ruixuan Xiao; Yiwen Dong 003; Lei Feng 006; Junbo Zhao 002 (CoRR, 2022)

Logit Clipping for Robust Learning against Label Noise. - Hongxin Wei; Huiping Zhuang; Renchunzi Xie; Lei Feng 006; Gang Niu 001; Bo An 001; Yixuan Li 001 (CoRR, 2022)

Regularized Matrix Factorization for Multilabel Learning With Missing Labels. - Lei Feng 006; Jun Huang 003; Senlin Shu; Bo An 001 (IEEE Trans. Cybern., 2022)

SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning. - Zhuowei Wang 003; Jing Jiang 002; Bo Han 003; Lei Feng 006; Bo An 001; Gang Niu 001; Guodong Long (Trans. Mach. Learn. Res., 2022)

Partial-Label Regression. - Xin Cheng 007; Deng-Bao Wang; Lei Feng 006; Min-Ling Zhang; Bo An 001 (AAAI, 2023)

A Generalized Unbiased Risk Estimator for Learning with Augmented Classes. - Senlin Shu; Shuo He 001; Haobo Wang 001; Hongxin Wei; Tao Xiang 001; Lei Feng 006 (AAAI, 2023)

Consistent Complementary-Label Learning via Order-Preserving Losses. - Shuqi Liu 002; Yuzhou Cao; Qiaozhen Zhang; Lei Feng 006; Bo An 001 (AISTATS, 2023)

Fine-Grained Classification with Noisy Labels. - Qi Wei 004; Lei Feng 006; Haoliang Sun; Ren Wang 011; Chenhui Guo; Yilong Yin (CVPR, 2023)

Candidate-aware Selective Disambiguation Based On Normalized Entropy for Instance-dependent Partial-label Learning. - Shuo He 001; Guowu Yang; Lei Feng 006 (ICCV, 2023)

Multi-Label Knowledge Distillation. - Penghui Yang 001; Ming-Kun Xie; Chen-Chen Zong; Lei Feng 006; Gang Niu 001; Masashi Sugiyama; Sheng-Jun Huang (ICCV, 2023)

Late Stopping: Avoiding Confidently Learning from Mislabeled Examples. - Suqin Yuan; Lei Feng 006; Tongliang Liu (ICCV, 2023)

Weakly Supervised Regression with Interval Targets. - Xin Cheng 007; Yuzhou Cao; Ximing Li 002; Bo An 001; Lei Feng 006 (ICML, 2023)

A Universal Unbiased Method for Classification from Aggregate Observations. - Zixi Wei; Lei Feng 006; Bo Han 003; Tongliang Liu; Gang Niu 001; Xiaofeng Zhu 001; Heng Tao Shen (ICML, 2023)

Mitigating Memorization of Noisy Labels by Clipping the Model Prediction. - Hongxin Wei; Huiping Zhuang; Renchunzi Xie; Lei Feng 006; Gang Niu 001; Bo An 001; Yixuan Li 001 (ICML, 2023)

ProMix: Combating Label Noise via Maximizing Clean Sample Utility. - Ruixuan Xiao; Yiwen Dong 003; Haobo Wang 001; Lei Feng 006; Runze Wu 001; Gang Chen 001; Junbo Zhao 002 (IJCAI, 2023)

Partial-label Learning with Mixed Closed-set and Open-set Out-of-candidate Examples. - Shuo He 001; Lei Feng 006; Guowu Yang (KDD, 2023)

In Defense of Softmax Parametrization for Calibrated and Consistent Learning to Defer. - Yuzhou Cao; Hussein Mozannar; Lei Feng 006; Hongxin Wei; Bo An 001 (NeurIPS, 2023)

Regression with Cost-based Rejection. - Xin Cheng 007; Yuzhou Cao; Haobo Wang 001; Hongxin Wei; Bo An 001; Lei Feng 006 (NeurIPS, 2023)

Binary Classification with Confidence Difference. - Wei Wang 373; Lei Feng 006; Yuchen Jiang; Gang Niu 001; Min-Ling Zhang; Masashi Sugiyama (NeurIPS, 2023)

SPA: A Graph Spectral Alignment Perspective for Domain Adaptation. - Zhiqing Xiao; Haobo Wang 001; Ying Jin; Lei Feng 006; Gang Chen 001; Fei Huang 002; Junbo Zhao 002 (NeurIPS, 2023)

On the Importance of Feature Separability in Predicting Out-Of-Distribution Error. - Renchunzi Xie; Hongxin Wei; Lei Feng 006; Yuzhou Cao; Bo An 001 (NeurIPS, 2023)

ALIM: Adjusting Label Importance Mechanism for Noisy Partial Label Learning. - Mingyu Xu; Zheng Lian; Lei Feng 006; Bin Liu 041; Jianhua Tao 001 (NeurIPS, 2023)

DALI: Dynamically Adjusted Label Importance for Noisy Partial Label Learning. - Mingyu Xu; Zheng Lian; Lei Feng 006; Bin Liu 042; Jianhua Tao 001 (CoRR, 2023)

Investigating and Mitigating the Side Effects of Noisy Views in Multi-view Clustering in Practical Scenarios. - Jie Xu 044; Gang Niu 001; Xiaolong Wang; Yazhou Ren 001; Lei Feng 006; Xiaoshuang Shi; Heng Tao Shen; Xiaofeng Zhu 001 (CoRR, 2023)

SDFReg: Learning Signed Distance Functions for Point Cloud Registration. - Leida Zhang; Yiqun Wang 001; Zhengda Lu; Lei Feng 006 (CoRR, 2023)

COMET: Convolutional Dimension Interaction for Collaborative Filtering. - Zhuoyi Lin; Lei Feng 006; Xingzhi Guo; Yu Zhang 084; Rui Yin 002; Chee Keong Kwoh 001; Chi Xu (ACM Trans. Intell. Syst. Technol., 2023)

Learning cross-domain semantic-visual relationships for transductive zero-shot learning. - Fengmao Lv; Jianyang Zhang; Guowu Yang; Lei Feng 006; Yufeng Yu; Lixin Duan (Pattern Recognit., 2023)

Multiple-Instance Learning From Unlabeled Bags With Pairwise Similarity. - Lei Feng 006; Senlin Shu; Yuzhou Cao; Lue Tao; Hongxin Wei; Tao Xiang 001; Bo An 001; Gang Niu 001 (IEEE Trans. Knowl. Data Eng., 2023)

Deep Learning From Multiple Noisy Annotators as A Union. - Hongxin Wei; Renchunzi Xie; Lei Feng 006; Bo Han 003; Bo An 001 (IEEE Trans. Neural Networks Learn. Syst., 2023)

Learning Geometry-Aware Representations for New Intent Discovery. - Kai Tang; Junbo Zhao 002; Xiao Ding; Runze Wu 001; Lei Feng 006; Gang Chen 001; Haobo Wang 001 (ACL (1), 2024)

Consistent Hierarchical Classification with A Generalized Metric. - Yuzhou Cao; Lei Feng 006; Bo An 001 (AISTATS, 2024)

Mitigating Underfitting in Learning to Defer with Consistent Losses. - Shuqi Liu 002; Yuzhou Cao; Qiaozhen Zhang; Lei Feng 006; Bo An 001 (AISTATS, 2024)

Positive-Unlabeled Learning by Latent Group-Aware Meta Disambiguation. - Lin Long; Haobo Wang 001; Zhijie Jiang; Lei Feng 006; Chang Yao; Gang Chen 001; Junbo Zhao 002 (CVPR, 2024)

CroSel: Cross Selection of Confident Pseudo Labels for Partial-Label Learning. - Shiyu Tian; Hongxin Wei; Yiqun Wang 001; Lei Feng 006 (CVPR, 2024)

Targeted Representation Alignment for Open-World Semi-Supervised Learning. - Ruixuan Xiao; Lei Feng 006; Kai Tang; Junbo Zhao 002; Yixuan Li 001; Gang Chen 001; Haobo Wang 001 (CVPR, 2024)

Investigating and Mitigating the Side Effects of Noisy Views for Self-Supervised Clustering Algorithms in Practical Multi-View Scenarios. - Jie Xu 044; Yazhou Ren 001; Xiaolong Wang; Lei Feng 006; Zheng Zhang 006; Gang Niu 001; Xiaofeng Zhu 001 (CVPR, 2024)

Candidate Label Set Pruning: A Data-centric Perspective for Deep Partial-label Learning. - Shuo He 001; Chaojie Wang 001; Guowu Yang; Lei Feng 006 (ICLR, 2024)

Consistent Multi-Class Classification from Multiple Unlabeled Datasets. - Zixi Wei; Senlin Shu; Yuzhou Cao; Hongxin Wei; Bo An 001; Lei Feng 006 (ICLR, 2024)

Early Stopping Against Label Noise Without Validation Data. - Suqin Yuan; Lei Feng 006; Tongliang Liu (ICLR, 2024)

On the Vulnerability of Adversarially Trained Models Against Two-faced Attacks. - Shengjie Zhou; Lue Tao; Yuzhou Cao; Tao Xiang 001; Bo An 001; Lei Feng 006 (ICLR, 2024)

Visual-Text Cross Alignment: Refining the Similarity Score in Vision-Language Models. - Jinhao Li 004; Haopeng Li; Sarah Monazam Erfani; Lei Feng 006; James Bailey 001; Feng Liu 003 (ICML, 2024)

A General Framework for Learning from Weak Supervision. - Hao Chen 102; Jindong Wang 001; Lei Feng 006; Xiang Li 106; Yidong Wang; Xing Xie 001; Masashi Sugiyama; Rita Singh; Bhiksha Raj (ICML, 2024)

Sample-specific Masks for Visual Reprogramming-based Prompting. - Chengyi Cai; Zesheng Ye; Lei Feng 006; Jianzhong Qi 001; Feng Liu 003 (ICML, 2024)

Positive and Unlabeled Learning with Controlled Probability Boundary Fence. - Changchun Li; Yuanchao Dai; Lei Feng 006; Ximing Li 002; Bing Wang 018; Jihong Ouyang (ICML, 2024)

Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss. - Zhenlong Liu; Lei Feng 006; Huiping Zhuang; Xiaofeng Cao; Hongxin Wei (ICML, 2024)

Exploiting Human-AI Dependence for Learning to Defer. - Zixi Wei; Yuzhou Cao; Lei Feng 006 (ICML, 2024)

Candidate Pseudolabel Learning: Enhancing Vision-Language Models by Prompt Tuning with Unlabeled Data. - Jiahan Zhang; Qi Wei 004; Feng Liu 003; Lei Feng 006 (ICML, 2024)

MacroHFT: Memory Augmented Context-aware Reinforcement Learning On High Frequency Trading. - Chuqiao Zong; Chaojie Wang 001; Molei Qin; Lei Feng 006; Xinrun Wang; Bo An 001 (KDD, 2024)

Bayesian-guided Label Mapping for Visual Reprogramming. - Chengyi Cai; Zesheng Ye; Lei Feng 006; Jianzhong Qi 001; Feng Liu 003 (NeurIPS, 2024)

keqing: knowledge-based question answering is a nature chain-of-thought mentor of LLM. - Chaojie Wang 001; Yishi Xu; Zhong Peng; Chenxi Zhang; Bo Chen 001; Xinrun Wang; Lei Feng 006; Bo An 001 (CoRR, 2024)

Debiased Sample Selection for Combating Noisy Labels. - Qi Wei 004; Lei Feng 006; Haobo Wang 001; Bo An 001 (CoRR, 2024)

Does Confidence Calibration Help Conformal Prediction? - Huajun Xi; Jianguo Huang; Lei Feng 006; Hongxin Wei (CoRR, 2024)

BDetCLIP: Multimodal Prompting Contrastive Test-Time Backdoor Detection. - Yuwei Niu; Shuo He 001; Qi Wei 004; Feng Liu 003; Lei Feng 006 (CoRR, 2024)

Automatic Dataset Construction (ADC): Sample Collection, Data Curation, and Beyond. - Minghao Liu 009; Zonglin Di; Jiaheng Wei; Zhongruo Wang; Hengxiang Zhang; Ruixuan Xiao; Haoyu Wang 001; Jinlong Pang; Hao Chen 102; Ankit Shah 001; Hongxin Wei; Xinlei He 001; et al. (CoRR, 2024)

ELU-GCN: Effectively Label-Utilizing Graph Convolutional Network. - Jincheng Huang 005; Yujie Mo; Xiaoshuang Shi; Lei Feng 006; Xiaofeng Zhu 001 (CoRR, 2024)

Dual-Head Knowledge Distillation: Enhancing Logits Utilization with an Auxiliary Head. - Penghui Yang 001; Chen-Chen Zong; Sheng-Jun Huang; Lei Feng 006; Bo An 001 (CoRR, 2024)

Rethinking Chain-of-Thought from the Perspective of Self-Training. - Zongqian Wu; Baoduo Xu; Ruochen Cui; Mengmeng Zhan; Xiaofeng Zhu 001; Lei Feng 006 (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)

PiCO+: Contrastive Label Disambiguation for Robust Partial Label Learning. - Haobo Wang 001; Ruixuan Xiao; Yixuan Li 001; Lei Feng 006; Gang Niu 001; Gang Chen 001; Junbo Zhao 002 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Multiple-instance Learning from Triplet Comparison Bags. - Senlin Shu; Deng-Bao Wang; Suqin Yuan; Hongxin Wei; Jiuchuan Jiang; Lei Feng 006; Min-Ling Zhang (ACM Trans. Knowl. Discov. Data, 2024)

Online binary classification from similar and dissimilar data. - Senlin Shu; Haobo Wang 001; Zhuowei Wang 003; Bo Han 003; Tao Xiang 001; Bo An 001; Lei Feng 006 (Mach. Learn., 2024)

Exploiting counter-examples for active learning with partial labels. - Fei Zhang; Yunjie Ye; Lei Feng 006; Zhongwen Rao; Jieming Zhu; Marcus Kalander; Chen Gong 002; Jianye Hao; Bo Han 003 (Mach. Learn., 2024)

On the Value of Head Labels in Multi-Label Text Classification. - Haobo Wang 001; Cheng Peng 011; Hede Dong; Lei Feng 006; Weiwei Liu 003; Tianlei Hu; Ke Chen 005; Gang Chen 001 (ACM Trans. Knowl. Discov. Data, 2024)

Learning sample-aware threshold for semi-supervised learning. - Qi Wei 004; Lei Feng 006; Haoliang Sun; Ren Wang 011; Rundong He; Yilong Yin (Mach. Learn., 2024)

Correction: Learning sample-aware threshold for semi-supervised learning. - Qi Wei 004; Lei Feng 006; Haoliang Sun; Ren Wang 011; Rundong He; Yilong Yin (Mach. Learn., 2024)

Influence-Based Fair Selection for Sample-Discriminative Backdoor Attack. - Qi Wei 004; Shuo He 001; Jiahan Zhang; Lei Feng 006; Bo An 001 (AAAI, 2025)

Improving Generalization of Deep Neural Networks by Optimum Shifting. - Yuyan Zhou; Ye Li; Lei Feng 006; Sheng-Jun Huang (AAAI, 2025)

Attribute-based Visual Reprogramming for Vision-Language Models. - Chengyi Cai; Zesheng Ye; Lei Feng 006; Jianzhong Qi 001; Feng Liu 003 (ICLR, 2025)

Instance-dependent Early Stopping. - Suqin Yuan; Runqi Lin; Lei Feng 006; Bo Han 003; Tongliang Liu (ICLR, 2025)

Endowing Visual Reprogramming with Adversarial Robustness. - Shengjie Zhou; Xin Cheng 007; Haiyang Xu 001; Ming Yan 008; Tao Xiang 001; Feng Liu 003; Lei Feng 006 (ICLR, 2025)

AsyCo: an asymmetric dual-task co-training model for partial-label learning. - Beibei Li 001; Yiyuan Zheng; Beihong Jin; Tao Xiang 001; Haobo Wang 001; Lei Feng 006 (Sci. China Inf. Sci., 2025)

Exploring Weak-to-Strong Generalization for CLIP-based Classification. - Jinhao Li 004; Sarah Monazam Erfani; Lei Feng 006; James Bailey 001; Feng Liu 003 (Trans. Mach. Learn. Res., 2025)

Does confidence calibration improve conformal prediction? - Huajun Xi; Jianguo Huang; Kangdao Liu; Lei Feng 006; Hongxin Wei (Trans. Mach. Learn. Res., 2025)

Towards Robust Incremental Learning under Ambiguous Supervision. - Rui Wang 076; Mingxuan Xia; Chang Yao; Lei Feng 006; Junbo Zhao 002; Gang Chen 001; Haobo Wang 001 (CoRR, 2025)

Attribute-based Visual Reprogramming for Image Classification with CLIP. - Chengyi Cai; Zesheng Ye; Lei Feng 006; Jianzhong Qi 001; Feng Liu 003 (CoRR, 2025)

Enhancing Sample Selection by Cutting Mislabeled Easy Examples. - Suqin Yuan; Lei Feng 006; Bo Han 003; Tongliang Liu (CoRR, 2025)

Is Depth All You Need? An Exploration of Iterative Reasoning in LLMs. - Zongqian Wu; Tianyu Li; Baoduo Xu; Jiaying Yang; Mengmeng Zhan; Xiaofeng Zhu 001; Lei Feng 006 (CoRR, 2025)

Variational Rectification Inference for Learning with Noisy Labels. - Haoliang Sun; Qi Wei 004; Lei Feng 006; Yupeng Hu; Fan Liu 008; Hehe Fan; Yilong Yin (Int. J. Comput. Vis., 2025)

Correction: Variational Rectification Inference for Learning with Noisy Labels. - Haoliang Sun; Qi Wei 004; Lei Feng 006; Yupeng Hu; Fan Liu 008; Hehe Fan; Yilong Yin (Int. J. Comput. Vis., 2025)

Establishing Linear Surrogate Regret Bounds for Convex Smooth Losses via Convolutional Fenchel-Young Losses. - Yuzhou Cao; Han Bao; Lei Feng 006; Bo An 001 (CoRR, 2025)

The Final Layer Holds the Key: A Unified and Efficient GNN Calibration Framework. - Jincheng Huang 005; Jie Xu 044; Xiaoshuang Shi; Ping Hu 001; Lei Feng 006; Xiaofeng Zhu 001 (CoRR, 2025)

GUARD: Generation-time LLM Unlearning via Adaptive Restriction and Detection. - Zhijie Deng; Chris Yuhao Liu; Zirui Pang; Xinlei He 001; Lei Feng 006; Qi Xuan; Zhaowei Zhu; Jiaheng Wei (CoRR, 2025)

Understanding Model Reprogramming for CLIP via Decoupling Visual Prompts. - Chengyi Cai; Zesheng Ye; Lei Feng 006; Jianzhong Qi 001; Feng Liu 003 (CoRR, 2025)

Neural Network Reprogrammability: A Unified Theme on Model Reprogramming, Prompt Tuning, and Prompt Instruction. - Zesheng Ye; Chengyi Cai; Ruijiang Dong; Jianzhong Qi 001; Lei Feng 006; Pin-Yu Chen; Feng Liu 003 (CoRR, 2025)

What Makes "Good" Distractors for Object Hallucination Evaluation in Large Vision-Language Models? - Ming-Kun Xie; Jiahao Xiao; Gang Niu 001; Lei Feng 006; Zhiqiang Kou; Min-Ling Zhang; Masashi Sugiyama (CoRR, 2025)