Xiaoqian Wang - RankMe

75 papers A* 35A 3B 1Misc 1Journal 26Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	The Trojan in the Vocabulary: Stealthy Sabotage of LLM Composition. CoRR Xiaoze Liu, Weichen Yu, Matt Fredrikson, Xiaoqian Wang, Jing Gao
2026	J	`jnl`	The Vision Wormhole: Latent-Space Communication in Heterogeneous Multi-Agent Systems. CoRR Xiaoze Liu, Ruowang Zhang, Weichen Yu, Siheng Xiong, Liu He, Feijie Wu, Hoin Jung, Matt Fredrikson, Xiaoqian Wang, Jing Gao
2025	A*	`conf`	Adversarial Latent Feature Augmentation for Fairness. ICLR Hoin Jung, Junyi Chai, Xiaoqian Wang
2025	A*	`conf`	Identifying and Mitigating Spurious Correlation in Multi-Task Learning. CVPR Junyi Chai, Shenyu Lu, Xiaoqian Wang
2025	A*	`conf`	Mitigating Spurious Correlations in Zero-Shot Multimodal Models. ICLR Shenyu Lu, Junyi Chai, Xiaoqian Wang
2025	A*	`conf`	On the Alignment between Fairness and Accuracy: from the Perspective of Adversarial Robustness. ICML Junyi Chai, Taeuk Jang, Jing Gao, Xiaoqian Wang
2025	J	`jnl`	SUV: Scalable Large Language Model Copyright Compliance with Regularized Selective Unlearning. CoRR Tianyang Xu, Xiaoze Liu, Feijie Wu, Xiaoqian Wang, Jing Gao
2025	A	`conf`	Towards On-the-Fly Novel Category Discovery in Dynamic Long-Tailed Distributions. WACV Hoin Jung, Xiaoqian Wang
2024	A*	`conf`	A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks. NeurIPS Hoin Jung, Taeuk Jang, Xiaoqian Wang
2024	J	`jnl`	A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks. CoRR Hoin Jung, Taeuk Jang, Xiaoqian Wang
2024	A	`conf`	Achieving Fairness through Separability: A Unified Framework for Fair Representation Learning. AISTATS Taeuk Jang, Hongchang Gao, Pengyi Shi, Xiaoqian Wang
2024	A*	`conf`	Adversarial Fairness Network. AAAI Taeuk Jang, Xiaoqian Wang, Heng Huang
2024	A*	`conf`	Auto- Train-Once: Controller Network Guided Automatic Network Pruning from Scratch. CVPR Xidong Wu, Shangqian Gao, Zeyu Zhang, Zhenzhen Li, Runxue Bao, Yanfu Zhang, Xiaoqian Wang, Heng Huang
2024	J	`jnl`	Auto-Train-Once: Controller Network Guided Automatic Network Pruning from Scratch. CoRR Xidong Wu, Shangqian Gao, Zeyu Zhang, Zhenzhen Li, Runxue Bao, Yanfu Zhang, Xiaoqian Wang, Heng Huang
2024	A*	`conf`	Benchmarking Deletion Metrics with the Principled Explanations. ICML Yipei Wang, Xiaoqian Wang
2024	A*	`conf`	Cumulative Difference Learning VAE for Time-Series with Temporally Correlated Inflow-Outflow. AAAI Tianchun Li, Chengxiang Wu, Pengyi Shi, Xiaoqian Wang
2024	A*	`conf`	Debiasing Attention Mechanism in Transformer without Demographics. ICLR Shenyu Lu, Yipei Wang, Xiaoqian Wang
2024	J	`jnl`	Evaluating the Factuality of Large Language Models using Large-Scale Knowledge Graphs. CoRR Xiaoze Liu, Feijie Wu, Tianyang Xu, Zhuo Chen, Yichi Zhang, Xiaoqian Wang, Jing Gao
2024	J	`jnl`	Evaluating the Factuality of Large Language Models using Large-Scale Knowledge Graphs. IEEE Data Eng. Bull. Xiaoze Liu, Feijie Wu, Tianyang Xu, Zhuo Chen, Yichi Zhang, Xiaoqian Wang, Jing Gao
2024	A*	`conf`	FADES: Fair Disentanglement with Sensitive Relevance. CVPR Taeuk Jang, Xiaoqian Wang
2024	—	`conf`	Fairness-Aware Online Positive-Unlabeled Learning. EMNLP (Industry Track) Hoin Jung, Xiaoqian Wang
2024	—	`conf`	Inverse Problem Antidote (IPA): Modeling of Systems Biology Model with Invertible Neural Networks. BIBM Linlin Li, Shenyu Lu, David M. Umulis, Xiaoqian Wang
2024	—	`conf`	Learning the Irreversible Progression Trajectory of Alzheimer's Disease. ISBI Yipei Wang, Bing He, Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, Xiaoqian Wang
2024	J	`jnl`	Learning the irreversible progression trajectory of Alzheimer's disease. CoRR Yipei Wang, Bing He, Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, Xiaoqian Wang
2024	A*	`conf`	Neural Collapse Inspired Debiased Representation Learning for Min-max Fairness. KDD Shenyu Lu, Junyi Chai, Xiaoqian Wang
2024	A	`conf`	On the Effect of Key Factors in Spurious Correlation: A theoretical Perspective. AISTATS Yipei Wang, Xiaoqian Wang
2024	A*	`conf`	SHIELD: Evaluation and Defense Strategies for Copyright Compliance in LLM Text Generation. EMNLP Xiaoze Liu, Ting Sun, Tianyang Xu, Feijie Wu, Cunxiang Wang, Xiaoqian Wang, Jing Gao
2024	J	`jnl`	SHIELD: Evaluation and Defense Strategies for Copyright Compliance in LLM Text Generation. CoRR Xiaoze Liu, Ting Sun, Tianyang Xu, Feijie Wu, Cunxiang Wang, Xiaoqian Wang, Jing Gao
2023	A*	`conf`	Difficulty-Based Sampling for Debiased Contrastive Representation Learning. CVPR Taeuk Jang, Xiaoqian Wang
2023	J	`jnl`	Iteratively Re-Weighted Method for Sparsity-Inducing Norms. IEEE Trans. Knowl. Data Eng. Feiping Nie, Zhanxuan Hu, Xiaoqian Wang, Xuelong Li, Heng Huang
2023	A*	`conf`	SimFair: A Unified Framework for Fairness-Aware Multi-Label Classification. AAAI Tianci Liu, Haoyu Wang, Yaqing Wang, Xiaoqian Wang, Lu Su, Jing Gao
2023	J	`jnl`	SimFair: A Unified Framework for Fairness-Aware Multi-Label Classification. CoRR Tianci Liu, Haoyu Wang, Yaqing Wang, Xiaoqian Wang, Lu Su, Jing Gao
2023	J	`jnl`	To be Robust and to be Fair: Aligning Fairness with Robustness. CoRR Junyi Chai, Xiaoqian Wang
2023	J	`jnl`	Towards Trustworthy Artificial Intelligence for Equitable Global Health. CoRR Hong Qin, Jude Kong, Wandi Ding, Ramneek Ahluwalia, Christo El-Morr, Zeynep Engin, Jake Okechukwu Effoduh, Rebecca Hwa, Serena Jingchuan Guo, Laleh Seyyed-Kalantari, Sylvia Kiwuwa Muyingo, Candace Makeda Moore, Ravi Parikh, Reva Schwartz, Dongxiao Zhu, Xiaoqian Wang, Yiye Zhang
2022	A*	`conf`	"Why Not Other Classes?": Towards Class-Contrastive Back-Propagation Explanations. NeurIPS Yipei Wang, Xiaoqian Wang
2022	J	`jnl`	A Unified Study of Machine Learning Explanation Evaluation Metrics. CoRR Yipei Wang, Xiaoqian Wang
2022	A*	`conf`	Fairness with Adaptive Weights. ICML Junyi Chai, Xiaoqian Wang
2022	A*	`conf`	Fairness without Demographics through Knowledge Distillation. NeurIPS Junyi Chai, Taeuk Jang, Xiaoqian Wang
2022	A*	`conf`	Group-Aware Threshold Adaptation for Fair Classification. AAAI Taeuk Jang, Pengyi Shi, Xiaoqian Wang
2022	A*	`conf`	Self-Supervised Fair Representation Learning without Demographics. NeurIPS Junyi Chai, Xiaoqian Wang
2021	A*	`conf`	Constructing a Fair Classifier with Generated Fair Data. AAAI Taeuk Jang, Feng Zheng, Xiaoqian Wang
2021	J	`jnl`	Group-Aware Threshold Adaptation for Fair Classification. CoRR Taeuk Jang, Pengyi Shi, Xiaoqian Wang
2021	Misc	`conf`	Multi-Task Learning Via Sharing Inexact Low-Rank Subspace. ICASSP Xiaoqian Wang, Feiping Nie
2021	A*	`conf`	On the Convergence of Stochastic Compositional Gradient Descent Ascent Method. IJCAI Hongchang Gao, Xiaoqian Wang, Lei Luo, Xinghua Shi
2021	A*	`conf`	Self-Interpretable Model with Transformation Equivariant Interpretation. NeurIPS Yipei Wang, Xiaoqian Wang
2021	J	`jnl`	Self-Interpretable Model with TransformationEquivariant Interpretation. CoRR Yipei Wang, Xiaoqian Wang
2021	A*	`conf`	Shapley Explanation Networks. ICLR Rui Wang, Xiaoqian Wang, David I. Inouye
2021	J	`jnl`	Shapley Explanation Networks. CoRR Rui Wang, Xiaoqian Wang, David I. Inouye
2020	J	`jnl`	Modeling Complex Spatial Patterns with Temporal Features via Heterogenous Graph Embedding Networks. CoRR Yida Huang, Haoyan Xu, Ziheng Duan, Anni Ren, Jie Feng, Qianru Zhang, Xiaoqian Wang
2020	J	`jnl`	Multivariate Time Series Classification with Hierarchical Variational Graph Pooling. CoRR Haoyan Xu, Ziheng Duan, Yunsheng Bai, Yida Huang, Anni Ren, Qianru Yu, Qianru Zhang, Yueyang Wang, Xiaoqian Wang, Yizhou Sun, Wei Wang
2020	J	`jnl`	Parallel Extraction of Long-term Trends and Short-term Fluctuation Framework for Multivariate Time Series Forecasting. CoRR Haoyan Xu, Ziheng Duan, Yida Huang, Jie Feng, Anni Ren, Qianru Zhang, Pengyu Song, Xiaoqian Wang
2020	A*	`conf`	Super-Resolution and Inpainting with Degraded and Upgraded Generative Adversarial Networks. IJCAI Yawen Huang, Feng Zheng, Danyang Wang, Junyu Jiang, Xiaoqian Wang, Ling Shao
2019	J	`jnl`	An Iteratively Re-weighted Method for Problems with Sparsity-Inducing Norms. CoRR Feiping Nie, Zhanxuan Hu, Xiaoqian Wang, Rong Wang, Xuelong Li, Heng Huang
2019	J	`jnl`	Approaching Machine Learning Fairness through Adversarial Network. CoRR Xiaoqian Wang, Heng Huang
2019	A*	`conf`	Balanced Self-Paced Learning for Generative Adversarial Clustering Network. CVPR Kamran Ghasedi, Xiaoqian Wang, Cheng Deng, Heng Huang
2018	J	`jnl`	Cognitive Assessment Prediction in Alzheimer's Disease by Multi-Layer Multi-Target Regression. Neuroinformatics Xiaoqian Wang, Xiantong Zhen, Quanzheng Li, Dinggang Shen, Heng Huang
2018	J	`jnl`	Conditional generative adversarial network for gene expression inference. Bioinform. Xiaoqian Wang, Kamran Ghasedi Dizaji, Heng Huang
2018	A*	`conf`	Directional Label Rectification in Adaptive Graph. AAAI Xiaoqian Wang, Hao Huang
2018	J	`jnl`	Longitudinal Genotype-Phenotype Association Study through Temporal Structure Auto-Learning Predictive Model. J. Comput. Biol. Xiaoqian Wang, Jingwen Yan, Xiaohui Yao, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Heng Huang
2018	A*	`conf`	New Balanced Active Learning Model and Optimization Algorithm. IJCAI Xiaoqian Wang, Yijun Huang, Ji Liu, Heng Huang
2018	J	`jnl`	Quantitative trait loci identification for brain endophenotypes via new additive model with random networks. Bioinform. Xiaoqian Wang, Hong Chen, Jingwen Yan, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Heng Huang
2018	A*	`conf`	Semi-Supervised Generative Adversarial Network for Gene Expression Inference. KDD Kamran Ghasedi Dizaji, Xiaoqian Wang, Heng Huang
2018	—	`conf`	Temporal Correlation Structure Learning for MCI Conversion Prediction. MICCAI (3) Xiaoqian Wang, Weidong Cai, Dinggang Shen, Heng Huang
2017	—	`conf`	Group Sparse Additive Machine. NIPS Hong Chen, Xiaoqian Wang, Cheng Deng, Heng Huang
2017	—	`conf`	Learning A Structured Optimal Bipartite Graph for Co-Clustering. NIPS Feiping Nie, Xiaoqian Wang, Cheng Deng, Heng Huang
2017	B	`conf`	Longitudinal Genotype-Phenotype Association Study via Temporal Structure Auto-learning Predictive Model. RECOMB Xiaoqian Wang, Jingwen Yan, Xiaohui Yao, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Heng Huang
2017	A*	`conf`	Multiclass Capped ℓp-Norm SVM for Robust Classifications. AAAI Feiping Nie, Xiaoqian Wang, Heng Huang
2017	—	`conf`	Predicting Interrelated Alzheimer's Disease Outcomes via New Self-learned Structured Low-Rank Model. IPMI Xiaoqian Wang, Kefei Liu, Jingwen Yan, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Heng Huang
2017	—	`conf`	Regularized Modal Regression with Applications in Cognitive Impairment Prediction. NIPS Xiaoqian Wang, Hong Chen, Weidong Cai, Dinggang Shen, Heng Huang
2016	A*	`conf`	New Robust Clustering Model for Identifying Cancer Genome Landscapes. ICDM Hongchang Gao, Xiaoqian Wang, Heng Huang
2016	—	`conf`	Prediction of Memory Impairment with MRI Data: A Longitudinal Study of Alzheimer's Disease. MICCAI (1) Xiaoqian Wang, Dinggang Shen, Heng Huang
2016	A*	`conf`	Structured Doubly Stochastic Matrix for Graph Based Clustering: Structured Doubly Stochastic Matrix. KDD Xiaoqian Wang, Feiping Nie, Heng Huang
2016	A*	`conf`	The Constrained Laplacian Rank Algorithm for Graph-Based Clustering. AAAI Feiping Nie, Xiaoqian Wang, Michael I. Jordan, Heng Huang
2015	A*	`conf`	Discriminative Unsupervised Dimensionality Reduction. IJCAI Xiaoqian Wang, Yun Liu, Feiping Nie, Heng Huang
2014	A*	`conf`	Clustering and projected clustering with adaptive neighbors. KDD Feiping Nie, Xiaoqian Wang, Heng Huang