Hao Wang

178 papers A* 53A 7Journal 104Unranked 14
YearRankTypeTitle / Venue / Authors
2026 A* conf
BayesAgent: Bayesian Agentic Reasoning Under Uncertainty via Verbalized Probabilistic Graphical Modeling.
AAAI
Hengguan Huang, Xing Shen, Guang-Yuan Hao, Songtao Wang, Lingfa Meng, Dianbo Liu, David A. Duchêne, Hao Wang, Samir Bhatt
2026 J jnl
CLEAR-HPV: Interpretable Concept Discovery for HPV-Associated Morphology in Whole-Slide Histology.
CoRR
Weiyi Qin, Yingci Liu-Swetz, Shiwei Tan, Hao Wang
2026 J jnl
Causal Decoding for Hallucination-Resistant Multimodal Large Language Models.
CoRR
Shiwei Tan, Hengyi Wang, Weiyi Qin, Qi Xu, Zhigang Hua, Hao Wang
2026 J jnl
Continual Learning of Large Language Models: A Comprehensive Survey.
ACM Comput. Surv.
Haizhou Shi, Zihao Xu, Hengyi Wang, Weiyi Qin, Wenyuan Wang, Yibin Wang, Zifeng Wang, Sayna Ebrahimi, Hao Wang
2026 J jnl
Reliable and Responsible Foundation Models: A Comprehensive Survey.
CoRR
Xinyu Yang, Junlin Han, Rishi Bommasani, Jinqi Luo, Wenjie Qu, Wangchunshu Zhou, Adel Bibi, Xiyao Wang, Jaehong Yoon, Elias Stengel-Eskin, Shengbang Tong, Lingfeng Shen, Rafael Rafailov, Runjia Li, Zhaoyang Wang, Yiyang Zhou, Chenhang Cui, Yu Wang, Wenhao Zheng, Huichi Zhou, Jindong Gu, Zhaorun Chen, Peng Xia, Tony Lee, Thomas P. Zollo, Vikash Sehwag, Jixuan Leng, Jiuhai Chen, Yuxin Wen, Huan Zhang, Zhun Deng, Linjun Zhang, Pavel Izmailov, Pang Wei Koh, Yulia Tsvetkov, Andrew Wilson, Jiaheng Zhang, James Zou, Cihang Xie, Hao Wang, Philip Torr, Julian J. McAuley, David Alvarez-Melis, Florian Tramèr, Kaidi Xu, Suman Jana, Chris Callison-Burch, René Vidal, Filippos Kokkinos, Mohit Bansal, Beidi Chen, Huaxiu Yao
2026 J jnl
S2D2: Fast Decoding for Diffusion LLMs via Training-Free Self-Speculation.
CoRR
Ligong Han, Hao Wang, Han Gao, Kai Xu, Akash Srivastava
2026 J jnl
T3D: Few-Step Diffusion Language Models via Trajectory Self-Distillation with Direct Discriminative Optimization.
CoRR
Tunyu Zhang, Xinxi Zhang, Ligong Han, Haizhou Shi, Xiaoxiao He, Zhuowei Li, Hao Wang, Kai Xu, Akash Srivastava, Hao Wang, Vladimir Pavlovic, Dimitris N. Metaxas
2026 A conf
Taming Latency-Memory Trade-Off in MoE-Based LLM Serving via Fine-Grained Expert Offloading.
EuroSys
Hanfei Yu, Xingqi Cui, Hong Zhang, Hao Wang, Hao Wang
2025 J jnl
Chronos-2: From Univariate to Universal Forecasting.
CoRR
Abdul Fatir Ansari, Oleksandr Shchur, Jaris Küken, Andreas Auer, Boran Han, Pedro Mercado, Syama Sundar Rangapuram, Huibin Shen, Lorenzo Stella, Xiyuan Zhang, Mononito Goswami, Shubham Kapoor, Danielle C. Maddix, Pablo Guerron, Tony Hu, Junming Yin, Nick Erickson, Prateek Mutalik Desai, Hao Wang, Huzefa Rangwala, George Karypis, Yuyang Wang, Michael Bohlke-Schneider
2025 A* conf
Concept-Based Unsupervised Domain Adaptation.
ICML
Xinyue Xu, Yueying Hu, Hui Tang, Yi Qin, Lu Mi, Hao Wang, Xiaomeng Li
2025 J jnl
Concept-Based Unsupervised Domain Adaptation.
CoRR
Xinyue Xu, Yueying Hu, Hui Tang, Yi Qin, Lu Mi, Hao Wang, Xiaomeng Li
2025 J jnl
Does Multimodality Lead to Better Time Series Forecasting?
CoRR
Xiyuan Zhang, Boran Han, Haoyang Fang, Abdul Fatir Ansari, Shuai Zhang, Danielle C. Maddix, Cuixiong Hu, Andrew Gordon Wilson, Michael W. Mahoney, Hao Wang, Yan Liu, Huzefa Rangwala, George Karypis, Bernie Wang
2025 J jnl
Effectively Steer LLM To Follow Preference via Building Confident Directions.
CoRR
Bingqing Song, Boran Han, Shuai Zhang, Hao Wang, Haoyang Fang, Bonan Min, Yuyang Wang, Mingyi Hong
2025 A* conf
GenVP: Generating Visual Puzzles with Contrastive Hierarchical VAEs.
ICLR
Kalliopi Basioti, Pritish Sahu, Tony Qingze Liu, Zihao Xu, Hao Wang, Vladimir Pavlovic
2025 J jnl
GenVP: Generating Visual Puzzles with Contrastive Hierarchical VAEs.
CoRR
Kalliopi Basioti, Pritish Sahu, Tony Qingze Liu, Zihao Xu, Hao Wang, Vladimir Pavlovic
2025 J jnl
Graph-Guided Dual-Level Augmentation for 3D Scene Segmentation.
CoRR
Hongbin Lin, Yifan Jiang, Juangui Xu, Jesse Jiaxi Xu, Yi Lu, Zhengyu Hu, Ying-Cong Chen, Hao Wang
2025 A* conf
Implicit In-context Learning.
ICLR
Zhuowei Li, Zihao Xu, Ligong Han, Yunhe Gao, Song Wen, Di Liu, Hao Wang, Dimitris N. Metaxas
2025 J jnl
Lossless Token Sequence Compression via Meta-Tokens.
CoRR
John Harvill, Ziwei Fan, Hao Wang, Yizhou Sun, Hao Ding, Luke Huan, Anoop Deoras
2025 — conf
Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal Large Language Models.
NAACL (Long Papers)
Hengyi Wang, Haizhou Shi, Shiwei Tan, Weiyi Qin, Wenyuan Wang, Tunyu Zhang, Akshay Nambi, Tanuja Ganu, Hao Wang
2025 A* conf
NetFormer: An interpretable model for recovering dynamical connectivity in neuronal population dynamics.
ICLR
Ziyu Lu, Wuwei Zhang, Trung Le, Hao Wang, Uygar Sümbül, Eric Todd Shea-Brown, Lu Mi
2025 A* conf
On Calibration of LLM-based Guard Models for Reliable Content Moderation.
ICLR
Hongfu Liu, Hengguan Huang, Xiangming Gu, Hao Wang, Ye Wang
2025 J jnl
PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation.
CoRR
Ziyan Wang, Sizhe Wei, Xiaoming Huo, Hao Wang
2025 J jnl
Reliable and Responsible Foundation Models.
Trans. Mach. Learn. Res.
Xinyu Yang, Junlin Han, Rishi Bommasani, Jinqi Luo, Wenjie Qu, Wangchunshu Zhou, Adel Bibi, Xiyao Wang, Jaehong Yoon, Elias Stengel-Eskin, Shengbang Tong, Lingfeng Shen, Rafael Rafailov, Runjia Li, Zhaoyang Wang, Yiyang Zhou, Chenhang Cui, Yu Wang, Wenhao Zheng, Huichi Zhou, Jindong Gu, Zhaorun Chen, Peng Xia, Tony Lee, Thomas P. Zollo, Vikash Sehwag, Jixuan Leng, Jiuhai Chen, Yuxin Wen, Huan Zhang, Zhun Deng, Linjun Zhang, Pavel Izmailov, Pang Wei Koh, Yulia Tsvetkov, Andrew Gordon Wilson, Jiaheng Zhang, James Zou, Cihang Xie, Hao Wang, Philip Torr, Julian J. McAuley, David Alvarez-Melis, Florian Tramèr, Kaidi Xu, Suman Jana, Chris Callison-Burch, René Vidal, Filippos Kokkinos, Mohit Bansal, Beidi Chen, Huaxiu Yao
2025 A conf
SODA: Spectral Orthogonal Decomposition Adaptation for Diffusion Models.
WACV
Xinxi Zhang, Song Wen, Ligong Han, Felix Juefei-Xu, Akash Srivastava, Junzhou Huang, Vladimir Pavlovic, Hao Wang, Molei Tao, Dimitris N. Metaxas
2025 J jnl
SQuat: Subspace-orthogonal KV Cache Quantization.
CoRR
Hao Wang, Ligong Han, Kai Xu, Akash Srivastava
2025 J jnl
Sculpting Subspaces: Constrained Full Fine-Tuning in LLMs for Continual Learning.
CoRR
Nikhil Shivakumar Nayak, Krishnateja Killamsetty, Ligong Han, Abhishek Bhandwaldar, Prateek Chanda, Kai Xu, Hao Wang, Aldo Pareja, Oleg Silkin, Mustafa Eyceoz, Akash Srivastava
2025 A* conf
The Hidden Life of Tokens: Reducing Hallucination of Large Vision-Language Models Via Visual Information Steering.
ICML
Zhuowei Li, Haizhou Shi, Yunhe Gao, Di Liu, Zhenting Wang, Yuxiao Chen, Ting Liu, Long Zhao, Hao Wang, Dimitris N. Metaxas
2025 J jnl
The Hidden Life of Tokens: Reducing Hallucination of Large Vision-Language Models via Visual Information Steering.
CoRR
Zhuowei Li, Haizhou Shi, Yunhe Gao, Di Liu, Zhenting Wang, Yuxiao Chen, Ting Liu, Long Zhao, Hao Wang, Dimitris N. Metaxas
2025 J jnl
Token-Level Uncertainty Estimation for Large Language Model Reasoning.
CoRR
Tunyu Zhang, Haizhou Shi, Yibin Wang, Hengyi Wang, Xiaoxiao He, Zhuowei Li, Haoxian Chen, Ligong Han, Kai Xu, Huan Zhang, Dimitris N. Metaxas, Hao Wang
2025 A* conf
Towards Domain Adaptive Neural Contextual Bandits.
ICLR
Ziyan Wang, Xiaoming Huo, Hao Wang
2025 A* conf
Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs.
ICLR
Aldo Pareja, Nikhil Shivakumar Nayak, Hao Wang, Krishnateja Killamsetty, Shivchander Sudalairaj, Wenlong Zhao, Seungwook Han, Abhishek Bhandwaldar, Guangxuan Xu, Kai Xu, Ligong Han, Luke Inglis, Akash Srivastava
2025 J jnl
Visual Sparse Steering: Improving Zero-shot Image Classification with Sparsity Guided Steering Vectors.
CoRR
Gerasimos Chatzoudis, Zhuowei Li, Gemma E. Moran, Hao Wang, Dimitris N. Metaxas
2025 J jnl
fMoE: Fine-Grained Expert Offloading for Large Mixture-of-Experts Serving.
CoRR
Hanfei Yu, Xingqi Cui, Hong Zhang, Hao Wang, Hao Wang
2024 J jnl
AutoFlow: Automated Workflow Generation for Large Language Model Agents.
CoRR
Zelong Li, Shuyuan Xu, Kai Mei, Wenyue Hua, Balaji Rama, Om Raheja, Hao Wang, He Zhu, Yongfeng Zhang
2024 A* conf
BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models.
NeurIPS
Yibin Wang, Haizhou Shi, Ligong Han, Dimitris N. Metaxas, Hao Wang
2024 J jnl
BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models.
CoRR
Yibin Wang, Haizhou Shi, Ligong Han, Dimitris N. Metaxas, Hao Wang
2024 — conf
Benchmarking Large Language Models on Communicative Medical Coaching: A Dataset and a Novel System.
ACL (Findings)
Hengguan Huang, Songtao Wang, Hongfu Liu, Hao Wang, Ye Wang
2024 J jnl
Benchmarking Large Language Models on Communicative Medical Coaching: a Novel System and Dataset.
CoRR
Hengguan Huang, Songtao Wang, Hongfu Liu, Hao Wang, Ye Wang
2024 J jnl
CDR: Customizable Density Ratios of Strong-over-weak LLMs for Preference Annotation.
CoRR
Guangxuan Xu, Kai Xu, Shivchander Sudalairaj, Hao Wang, Akash Srivastava
2024 J jnl
Chronos: Learning the Language of Time Series.
Trans. Mach. Learn. Res.
Abdul Fatir Ansari, Lorenzo Stella, Ali Caner Türkmen, Xiyuan Zhang, Pedro Mercado, Huibin Shen, Oleksandr Shchur, Syama Sundar Rangapuram, Sebastian Pineda-Arango, Shubham Kapoor, Jasper Zschiegner, Danielle C. Maddix, Hao Wang, Michael W. Mahoney, Kari Torkkola, Andrew Gordon Wilson, Michael Bohlke-Schneider, Bernie Wang
2024 A* conf
Composite Active Learning: Towards Multi-Domain Active Learning with Theoretical Guarantees.
AAAI
Guang-Yuan Hao, Hengguan Huang, Haotian Wang, Jie Gao, Hao Wang
2024 J jnl
Composite Active Learning: Towards Multi-Domain Active Learning with Theoretical Guarantees.
CoRR
Guang-Yuan Hao, Hengguan Huang, Haotian Wang, Jie Gao, Hao Wang
2024 J jnl
Continual Learning of Large Language Models: A Comprehensive Survey.
CoRR
Haizhou Shi, Zihao Xu, Hengyi Wang, Weiyi Qin, Wenyuan Wang, Yibin Wang, Hao Wang
2024 A* conf
Continuous Invariance Learning.
ICLR
Lin Yong, Fan Zhou, Lu Tan, Lintao Ma, Jianmeng Liu, Yansu He, Yuan Yuan, Yu Liu, James Y. Zhang, Yujiu Yang, Hao Wang
2024 A* conf
Delving into Differentially Private Transformer.
ICML
Youlong Ding, Xueyang Wu, Yining Meng, Yonggang Luo, Hao Wang, Weike Pan
2024 J jnl
Delving into Differentially Private Transformer.
CoRR
Youlong Ding, Xueyang Wu, Yining Meng, Yonggang Luo, Hao Wang, Weike Pan
2024 J jnl
Energy-Based Concept Bottleneck Models: Unifying Prediction, Concept Intervention, and Conditional Interpretations.
CoRR
Xinyue Xu, Yi Qin, Lu Mi, Hao Wang, Xiaomeng Li
2024 A* conf
Energy-Based Concept Bottleneck Models: Unifying Prediction, Concept Intervention, and Probabilistic Interpretations.
ICLR
Xinyue Xu, Yi Qin, Lu Mi, Hao Wang, Xiaomeng Li
2024 J jnl
Formal-LLM: Integrating Formal Language and Natural Language for Controllable LLM-based Agents.
CoRR
Zelong Li, Wenyue Hua, Hao Wang, He Zhu, Yongfeng Zhang
2024 J jnl
Implicit In-context Learning.
CoRR
Zhuowei Li, Zihao Xu, Ligong Han, Yunhe Gao, Song Wen, Di Liu, Hao Wang, Dimitris N. Metaxas
2024 — conf
LatticeGen: Hiding Generated Text in a Lattice for Privacy-Aware Large Language Model Generation on Cloud.
NAACL-HLT (Findings)
Mengke Zhang, Tianxing He, Tianle Wang, Lu Mi, Niloofar Mireshghallah, Binyi Chen, Hao Wang, Yulia Tsvetkov
2024 J jnl
Learning Unlabeled Clients Divergence for Federated Semi-Supervised Learning via Anchor Model Aggregation.
Trans. Mach. Learn. Res.
Marawan Elbatel, Hualiang Wang, Jixiang Chen, Hao Wang, Xiaomeng Li
2024 J jnl
Learning Unlabeled Clients Divergence via Anchor Model Aggregation for Federated Semi-supervised Learning.
CoRR
Marawan Elbatel, Hualiang Wang, Jixiang Chen, Hao Wang, Xiaomeng Li
2024 J jnl
Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal Large Language Models.
CoRR
Hengyi Wang, Haizhou Shi, Shiwei Tan, Weiyi Qin, Wenyuan Wang, Tunyu Zhang, Akshay Nambi, Tanuja Ganu, Hao Wang
2024 A* conf
Natural Counterfactuals With Necessary Backtracking.
NeurIPS
Guang-Yuan Hao, Jiji Zhang, Biwei Huang, Hao Wang, Kun Zhang
2024 J jnl
Natural Counterfactuals With Necessary Backtracking.
CoRR
Guang-Yuan Hao, Jiji Zhang, Biwei Huang, Hao Wang, Kun Zhang
2024 J jnl
On Calibration of LLM-based Guard Models for Reliable Content Moderation.
CoRR
Hongfu Liu, Hengguan Huang, Hao Wang, Xiangming Gu, Ye Wang
2024 A conf
Pre-trained Recommender Systems: A Causal Debiasing Perspective.
WSDM
Ziqian Lin, Hao Ding, Trong Nghia Hoang, Branislav Kveton, Anoop Deoras, Hao Wang
2024 A* conf
Probabilistic Conceptual Explainers: Trustworthy Conceptual Explanations for Vision Foundation Models.
ICML
Hengyi Wang, Shiwei Tan, Hao Wang
2024 J jnl
Probabilistic Conceptual Explainers: Trustworthy Conceptual Explanations for Vision Foundation Models.
CoRR
Hengyi Wang, Shiwei Tan, Hao Wang
2024 A* conf
Raidar: geneRative AI Detection viA Rewriting.
ICLR
Chengzhi Mao, Carl Vondrick, Hao Wang, Junfeng Yang
2024 J jnl
Raidar: geneRative AI Detection viA Rewriting.
CoRR
Chengzhi Mao, Carl Vondrick, Hao Wang, Junfeng Yang
2024 A conf
Second-Order Graph ODEs for Multi-Agent Trajectory Forecasting.
WACV
Song Wen, Hao Wang, Di Liu, Qilong Zhangli, Dimitris N. Metaxas
2024 J jnl
Spectrum-Aware Parameter Efficient Fine-Tuning for Diffusion Models.
CoRR
Xinxi Zhang, Song Wen, Ligong Han, Felix Juefei-Xu, Akash Srivastava, Junzhou Huang, Hao Wang, Molei Tao, Dimitris N. Metaxas
2024 J jnl
Towards Domain Adaptive Neural Contextual Bandits.
CoRR
Ziyan Wang, Hao Wang
2024 J jnl
Training-Free Bayesianization for Low-Rank Adapters of Large Language Models.
CoRR
Haizhou Shi, Yibin Wang, Ligong Han, Huan Zhang, Hao Wang
2024 J jnl
Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs.
CoRR
Aldo Pareja, Nikhil Shivakumar Nayak, Hao Wang, Krishnateja Killamsetty, Shivchander Sudalairaj, Wenlong Zhao, Seungwook Han, Abhishek Bhandwaldar, Guangxuan Xu, Kai Xu, Ligong Han, Luke Inglis, Akash Srivastava
2024 — conf
Variational Language Concepts for Interpreting Foundation Language Models.
EMNLP (Findings)
Hengyi Wang, Shiwei Tan, Zhiqing Hong, Desheng Zhang, Hao Wang
2024 J jnl
Variational Language Concepts for Interpreting Foundation Language Models.
CoRR
Hengyi Wang, Shiwei Tan, Zhiqing Hong, Desheng Zhang, Hao Wang
2024 J jnl
Verbalized Probabilistic Graphical Modeling with Large Language Models.
CoRR
Hengguan Huang, Xing Shen, Songtao Wang, Dianbo Liu, Hao Wang
2023 A* conf
A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm.
NeurIPS
Haizhou Shi, Hao Wang
2023 J jnl
A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm.
CoRR
Haizhou Shi, Hao Wang
2023 J jnl
Continuous Invariance Learning.
CoRR
Yong Lin, Fan Zhou, Lu Tan, Lintao Ma, Jiameng Liu, Yansu He, Yuan Yuan, Yu Liu, James Zhang, Yujiu Yang, Hao Wang
2023 A conf
Counterfactual Collaborative Reasoning.
WSDM
Jianchao Ji, Zelong Li, Shuyuan Xu, Max Xiong, Juntao Tan, Yingqiang Ge, Hao Wang, Yongfeng Zhang
2023 J jnl
Counterfactual Collaborative Reasoning.
CoRR
Jianchao Ji, Zelong Li, Shuyuan Xu, Max Xiong, Juntao Tan, Yingqiang Ge, Hao Wang, Yongfeng Zhang
2023 J jnl
Cross-Frequency Time Series Meta-Forecasting.
CoRR
Mike Van Ness, Huibin Shen, Hao Wang, Xiaoyong Jin, Danielle C. Maddix, Karthick Gopalswamy
2023 J jnl
DPFormer: Learning Differentially Private Transformer on Long-Tailed Data.
CoRR
Youlong Ding, Xueyang Wu, Hao Wang, Weike Pan
2023 A* conf
Domain-Indexing Variational Bayes: Interpretable Domain Index for Domain Adaptation.
ICLR
Zihao Xu, Guang-Yuan Hao, Hao He, Hao Wang
2023 J jnl
Domain-Indexing Variational Bayes: Interpretable Domain Index for Domain Adaptation.
CoRR
Zihao Xu, Guang-Yuan Hao, Hao He, Hao Wang
2023 A* conf
FedNP: Towards Non-IID Federated Learning via Federated Neural Propagation.
AAAI
Xueyang Wu, Hengguan Huang, Youlong Ding, Hao Wang, Ye Wang, Qian Xu
2023 A conf
Identifying Regional Driving Risks via Transductive Cross-City Transfer Learning Under Negative Transfer.
CIKM
Hua Yan, Hao Wang, Desheng Zhang, Yu Yang
2023 A* conf
Landscape Learning for Neural Network Inversion.
ICCV
Ruoshi Liu, Chengzhi Mao, Purva Tendulkar, Hao Wang, Carl Vondrick
2023 J jnl
LatticeGen: A Cooperative Framework which Hides Generated Text in a Lattice for Privacy-Aware Generation on Cloud.
CoRR
Mengke Zhang, Tianxing He, Tianle Wang, Lu Mi, Fatemehsadat Mireshghallah, Binyi Chen, Hao Wang, Yulia Tsvetkov
2023 J jnl
Pre-trained Recommender Systems: A Causal Debiasing Perspective.
CoRR
Ziqian Lin, Hao Ding, Nghia Hoang, Branislav Kveton, Anoop Deoras, Hao Wang
2023 A* conf
PreDiff: Precipitation Nowcasting with Latent Diffusion Models.
NeurIPS
Zhihan Gao, Xingjian Shi, Boran Han, Hao Wang, Xiaoyong Jin, Danielle C. Maddix, Yi Zhu, Mu Li, Yuyang Wang
2023 J jnl
PreDiff: Precipitation Nowcasting with Latent Diffusion Models.
CoRR
Zhihan Gao, Xingjian Shi, Boran Han, Hao Wang, Xiaoyong Jin, Danielle C. Maddix, Yi Zhu, Mu Li, Yuyang Wang
2023 A* conf
Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting.
NeurIPS
Marcel Kollovieh, Abdul Fatir Ansari, Michael Bohlke-Schneider, Jasper Zschiegner, Hao Wang, Yuyang Wang
2023 J jnl
Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting.
CoRR
Marcel Kollovieh, Abdul Fatir Ansari, Michael Bohlke-Schneider, Jasper Zschiegner, Hao Wang, Yuyang Wang
2023 J jnl
Rethinking Privacy Risks from Wireless Surveillance Camera.
ACM Trans. Sens. Networks
Qianyi Huang, Youjing Lu, Zhicheng Luo, Hao Wang, Fan Wu, Guihai Chen, Qian Zhang
2023 A* conf
Robust Perception through Equivariance.
ICML
Chengzhi Mao, Lingyu Zhang, Abhishek Vaibhav Joshi, Junfeng Yang, Hao Wang, Carl Vondrick
2023 A* conf
Self-Interpretable Time Series Prediction with Counterfactual Explanations.
ICML
Jingquan Yan, Hao Wang
2023 J jnl
Self-Interpretable Time Series Prediction with Counterfactual Explanations.
CoRR
Jingquan Yan, Hao Wang
2023 A* conf
Taxonomy-Structured Domain Adaptation.
ICML
Tianyi Liu, Zihao Xu, Hao He, Guang-Yuan Hao, Guang-He Lee, Hao Wang
2023 J jnl
Taxonomy-Structured Domain Adaptation.
CoRR
Tianyi Liu, Zihao Xu, Hao He, Guang-Yuan Hao, Guang-He Lee, Hao Wang
2023 A conf
Trending Now: Modeling Trend Recommendations.
RecSys
Hao Ding, Branislav Kveton, Yifei Ma, Youngsuk Park, Venkataramana Kini, Yupeng Gu, Ravi Divvela, Fei Wang, Anoop Deoras, Hao Wang
2023 J jnl
Variational Imbalanced Regression.
CoRR
Ziyan Wang, Hao Wang
2023 A* conf
Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothing.
NeurIPS
Ziyan Wang, Hao Wang
2022 A* conf
"My nose is running." "Are you also coughing?": Building A Medical Diagnosis Agent with Interpretable Inquiry Logics.
IJCAI
Wenge Liu, Yi Cheng, Hao Wang, Jianheng Tang, Yafei Liu, Ruihui Zhao, Wenjie Li, Yefeng Zheng, Xiaodan Liang
2022 J jnl
"My nose is running.""Are you also coughing?": Building A Medical Diagnosis Agent with Interpretable Inquiry Logics.
CoRR
Wenge Liu, Yi Cheng, Hao Wang, Jianheng Tang, Yafei Liu, Ruihui Zhao, Wenjie Li, Yefeng Zheng, Xiaodan Liang
2022 J jnl
1st ICLR International Workshop on Privacy, Accountability, Interpretability, Robustness, Reasoning on Structured Data (PAIR^2Struct).
CoRR
Hao Wang, Wanyu Lin, Hao He, Di Wang, Chengzhi Mao, Muhan Zhang
2022 A* conf
Bayesian Invariant Risk Minimization.
CVPR
Yong Lin, Hanze Dong, Hao Wang, Tong Zhang
2022 A* conf
Causal Transportability for Visual Recognition.
CVPR
Chengzhi Mao, Kevin Xia, James Wang, Hao Wang, Junfeng Yang, Elias Bareinboim, Carl Vondrick
2022 J jnl
Causal Transportability for Visual Recognition.
CoRR
Chengzhi Mao, Kevin Xia, James Wang, Hao Wang, Junfeng Yang, Elias Bareinboim, Carl Vondrick
2022 A* conf
Context Uncertainty in Contextual Bandits with Applications to Recommender Systems.
AAAI
Hao Wang, Yifei Ma, Hao Ding, Yuyang Wang
2022 J jnl
Context Uncertainty in Contextual Bandits with Applications to Recommender Systems.
CoRR
Hao Wang, Yifei Ma, Hao Ding, Yuyang Wang
2022 A* conf
Domain Adaptation for Time Series Forecasting via Attention Sharing.
ICML
Xiaoyong Jin, Youngsuk Park, Danielle C. Maddix, Hao Wang, Yuyang Wang
2022 J jnl
Domain Adaptation with Factorizable Joint Shift.
CoRR
Hao He, Yuzhe Yang, Hao Wang
2022 A* conf
Earthformer: Exploring Space-Time Transformers for Earth System Forecasting.
NeurIPS
Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu, Yuyang Wang, Mu Li, Dit-Yan Yeung
2022 J jnl
Earthformer: Exploring Space-Time Transformers for Earth System Forecasting.
CoRR
Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu, Yuyang Wang, Mu Li, Dit-Yan Yeung
2022 A* conf
Extrapolative Continuous-time Bayesian Neural Network for Fast Training-free Test-time Adaptation.
NeurIPS
Hengguan Huang, Xiangming Gu, Hao Wang, Chang Xiao, Hongfu Liu, Ye Wang
2022 J jnl
First De-Trend then Attend: Rethinking Attention for Time-Series Forecasting.
CoRR
Xiyuan Zhang, Xiaoyong Jin, Karthick Gopalswamy, Gaurav Gupta, Youngsuk Park, Xingjian Shi, Hao Wang, Danielle C. Maddix, Yuyang Wang
2022 A* conf
Graph-Relational Domain Adaptation.
ICLR
Zihao Xu, Hao He, Guang-He Lee, Bernie Wang, Hao Wang
2022 J jnl
Graph-Relational Domain Adaptation.
CoRR
Zihao Xu, Hao He, Guang-He Lee, Yuyang Wang, Hao Wang
2022 J jnl
Landscape Learning for Neural Network Inversion.
CoRR
Ruoshi Liu, Chengzhi Mao, Purva Tendulkar, Hao Wang, Carl Vondrick
2022 — conf
Learning Interacting Dynamic Systems with Neural Ordinary Differential Equations.
DDDAS
Song Wen, Hao Wang, Dimitris N. Metaxas
2022 J jnl
On Multi-Domain Long-Tailed Recognition, Generalization and Beyond.
CoRR
Yuzhe Yang, Hao Wang, Dina Katabi
2022 — conf
On Multi-Domain Long-Tailed Recognition, Imbalanced Domain Generalization and Beyond.
ECCV (20)
Yuzhe Yang, Hao Wang, Dina Katabi
2022 A* conf
OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks.
CVPR
Wanyu Lin, Hao Lan, Hao Wang, Baochun Li
2022 J jnl
Robust Perception through Equivariance.
CoRR
Chengzhi Mao, Lingyu Zhang, Abhishek Vaibhav Joshi, Junfeng Yang, Hao Wang, Carl Vondrick
2022 — conf
Social ODE: Multi-agent Trajectory Forecasting with Neural Ordinary Differential Equations.
ECCV (22)
Song Wen, Hao Wang, Dimitris N. Metaxas
2022 J jnl
Subgraph Frequency Distribution Estimation using Graph Neural Networks.
CoRR
Zhongren Chen, Xinyue Xu, Shengyi Jiang, Hao Wang, Lu Mi
2022 A* conf
Training-Free Uncertainty Estimation for Dense Regression: Sensitivity as a Surrogate.
AAAI
Lu Mi, Hao Wang, Yonglong Tian, Hao He, Nir Shavit
2022 J jnl
Unsupervised Mismatch Localization in Cross-Modal Sequential Data with Application to Mispronunciations Localization.
Trans. Mach. Learn. Res.
Wei Wei, Hengguan Huang, Xiangming Gu, Hao Wang, Ye Wang
2022 J jnl
Unsupervised Mismatch Localization in Cross-Modal Sequential Data.
CoRR
Wei Wei, Hengguan Huang, Xiangming Gu, Hao Wang, Ye Wang
2022 J jnl
Visual Prompt Tuning for Test-time Domain Adaptation.
CoRR
Yunhe Gao, Xingjian Shi, Yi Zhu, Hao Wang, Zhiqiang Tang, Xiong Zhou, Mu Li, Dimitris N. Metaxas
2021 J jnl
A Survey on Bayesian Deep Learning.
ACM Comput. Surv.
Hao Wang, Dit-Yan Yeung
2021 A* conf
Adversarial Attacks are Reversible with Natural Supervision.
ICCV
Chengzhi Mao, Mia Chiquier, Hao Wang, Junfeng Yang, Carl Vondrick
2021 J jnl
Adversarial Attacks are Reversible with Natural Supervision.
CoRR
Chengzhi Mao, Mia Chiquier, Hao Wang, Junfeng Yang, Carl Vondrick
2021 A* conf
Correcting Exposure Bias for Link Recommendation.
ICML
Shantanu Gupta, Hao Wang, Zachary C. Lipton, Yuyang Wang
2021 J jnl
Correcting Exposure Bias for Link Recommendation.
CoRR
Shantanu Gupta, Hao Wang, Zachary C. Lipton, Yuyang Wang
2021 A* conf
Delving into Deep Imbalanced Regression.
ICML
Yuzhe Yang, Kaiwen Zha, Ying-Cong Chen, Hao Wang, Dina Katabi
2021 J jnl
Delving into Deep Imbalanced Regression.
CoRR
Yuzhe Yang, Kaiwen Zha, Ying-Cong Chen, Hao Wang, Dina Katabi
2021 A* conf
Generative Interventions for Causal Learning.
CVPR
Chengzhi Mao, Augustine Cha, Amogh Gupta, Hao Wang, Junfeng Yang, Carl Vondrick
2021 J jnl
Learning Guided Electron Microscopy with Active Acquisition.
CoRR
Lu Mi, Hao Wang, Yaron Meirovitch, Richard Schalek, Srinivas C. Turaga, Jeff W. Lichtman, Aravinthan D. T. Samuel, Nir Shavit
2021 A* conf
Paint Transformer: Feed Forward Neural Painting with Stroke Prediction.
ICCV
Songhua Liu, Tianwei Lin, Dongliang He, Fu Li, Ruifeng Deng, Xin Li, Errui Ding, Hao Wang
2021 J jnl
Paint Transformer: Feed Forward Neural Painting with Stroke Prediction.
CoRR
Songhua Liu, Tianwei Lin, Dongliang He, Fu Li, Ruifeng Deng, Xin Li, Errui Ding, Hao Wang
2021 J jnl
Revisiting Latent-Space Interpolation via a Quantitative Evaluation Framework.
CoRR
Lu Mi, Tianxing He, Core Francisco Park, Hao Wang, Yue Wang, Nir Shavit
2021 A* conf
STRODE: Stochastic Boundary Ordinary Differential Equation.
ICML
Hengguan Huang, Hongfu Liu, Hao Wang, Chang Xiao, Ye Wang
2021 J jnl
STRODE: Stochastic Boundary Ordinary Differential Equation.
CoRR
Hengguan Huang, Hongfu Liu, Hao Wang, Chang Xiao, Ye Wang
2021 J jnl
Zero-Shot Recommender Systems.
CoRR
Hao Ding, Yifei Ma, Anoop Deoras, Yuyang Wang, Hao Wang
2020 J jnl
Authenticating On-Body IoT Devices: An Adversarial Learning Approach.
CoRR
Yong Huang, Wei Wang, Hao Wang, Tao Jiang, Qian Zhang
2020 J jnl
Authenticating On-Body IoT Devices: An Adversarial Learning Approach.
IEEE Trans. Wirel. Commun.
Yong Huang, Wei Wang, Hao Wang, Tao Jiang, Qian Zhang
2020 J jnl
BodyCompass: Monitoring Sleep Posture with Wireless Signals.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.
Shichao Yue, Yuzhe Yang, Hao Wang, Hariharan Rahul, Dina Katabi
2020 A* conf
Continuously Indexed Domain Adaptation.
ICML
Hao Wang, Hao He, Dina Katabi
2020 J jnl
Continuously Indexed Domain Adaptation.
CoRR
Hao Wang, Hao He, Dina Katabi
2020 A* conf
Deep Graph Random Process for Relational-Thinking-Based Speech Recognition.
ICML
Hengguan Huang, Fuzhao Xue, Hao Wang, Ye Wang
2020 J jnl
Deep Graph Random Process for Relational-Thinking-Based Speech Recognition.
CoRR
Hengguan Huang, Fuzhao Xue, Hao Wang, Ye Wang
2020 J jnl
Generative Interventions for Causal Learning.
CoRR
Chengzhi Mao, Amogh Gupta, Augustine Cha, Hao Wang, Junfeng Yang, Carl Vondrick
2020 — conf
Learning Guided Electron Microscopy with Active Acquisition.
MICCAI (5)
Lu Mi, Hao Wang, Yaron Meirovitch, Richard Schalek, Srinivas C. Turaga, Jeff W. Lichtman, Aravinthan D. T. Samuel, Nir Shavit
2019 A* conf
Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling.
AAAI
Hao Wang, Chengzhi Mao, Hao He, Mingmin Zhao, Tommi S. Jaakkola, Dina Katabi
2019 J jnl
Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling.
CoRR
Hao Wang, Chengzhi Mao, Hao He, Mingmin Zhao, Tommi S. Jaakkola, Dina Katabi
2019 — conf
ProbGAN: Towards Probabilistic GAN with Theoretical Guarantees.
ICLR (Poster)
Hao He, Hao Wang, Guang-He Lee, Yonglong Tian
2019 A* conf
Recurrent Poisson Process Unit for Speech Recognition.
AAAI
Hengguan Huang, Hao Wang, Brian Mak
2019 A* conf
Rethinking Knowledge Graph Propagation for Zero-Shot Learning.
CVPR
Michael Kampffmeyer, Yinbo Chen, Xiaodan Liang, Hao Wang, Yujia Zhang, Eric P. Xing
2019 — conf
Towards Motion Invariant Authentication for On-Body IoT Devices.
ICC
Yong Huang, Mengnian Xu, Wei Wang, Hao Wang, Tao Jiang, Qian Zhang
2019 J jnl
Towards Motion Invariant Authentication for On-Body IoT Devices.
CoRR
Yong Huang, Mengnian Xu, Wei Wang, Hao Wang, Tao Jiang, Qian Zhang
2019 J jnl
Training-Free Uncertainty Estimation for Neural Networks.
CoRR
Lu Mi, Hao Wang, Yonglong Tian, Nir Shavit
2018 J jnl
Extracting Multi-Person Respiration from Entangled RF Signals.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.
Shichao Yue, Hao He, Hao Wang, Hariharan Rahul, Dina Katabi
2018 J jnl
Rethinking Knowledge Graph Propagation for Zero-Shot Learning.
CoRR
Michael Kampffmeyer, Yinbo Chen, Xiaodan Liang, Hao Wang, Yujia Zhang, Eric P. Xing
2017 — conf
Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model.
NIPS
Xingjian Shi, Zhihan Gao, Leonard Lausen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, Wang-chun Woo
2017 J jnl
Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model.
CoRR
Xingjian Shi, Zhihan Gao, Leonard Lausen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, Wang-chun Woo
2017 A* conf
Relational Deep Learning: A Deep Latent Variable Model for Link Prediction.
AAAI
Hao Wang, Xingjian Shi, Dit-Yan Yeung
2017 J jnl
ZM-Net: Real-time Zero-shot Image Manipulation Network.
CoRR
Hao Wang, Xiaodan Liang, Hao Zhang, Dit-Yan Yeung, Eric P. Xing
2016 — conf
Collaborative Recurrent Autoencoder: Recommend while Learning to Fill in the Blanks.
NIPS
Hao Wang, Xingjian Shi, Dit-Yan Yeung
2016 J jnl
Collaborative Recurrent Autoencoder: Recommend while Learning to Fill in the Blanks.
CoRR
Hao Wang, Xingjian Shi, Dit-Yan Yeung
2016 — conf
Natural-Parameter Networks: A Class of Probabilistic Neural Networks.
NIPS
Hao Wang, Xingjian Shi, Dit-Yan Yeung
2016 J jnl
Natural-Parameter Networks: A Class of Probabilistic Neural Networks.
CoRR
Hao Wang, Xingjian Shi, Dit-Yan Yeung
2016 J jnl
Towards Bayesian Deep Learning: A Framework and Some Existing Methods.
CoRR
Hao Wang, Dit-Yan Yeung
2016 J jnl
Towards Bayesian Deep Learning: A Framework and Some Existing Methods.
IEEE Trans. Knowl. Data Eng.
Hao Wang, Dit-Yan Yeung
2016 J jnl
Towards Bayesian Deep Learning: A Survey.
CoRR
Hao Wang, Dit-Yan Yeung
2015 A* conf
Collaborative Deep Learning for Recommender Systems.
KDD
Hao Wang, Naiyan Wang, Dit-Yan Yeung
2015 — conf
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting.
NIPS
Xingjian Shi, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, Wang-chun Woo
2015 J jnl
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting.
CoRR
Xingjian Shi, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, Wang-chun Woo
2015 J jnl
Relational Collaborative Topic Regression for Recommender Systems.
IEEE Trans. Knowl. Data Eng.
Hao Wang, Wu-Jun Li
2015 A* conf
Relational Stacked Denoising Autoencoder for Tag Recommendation.
AAAI
Hao Wang, Xingjian Shi, Dit-Yan Yeung
2014 J jnl
Collaborative Deep Learning for Recommender Systems.
CoRR
Hao Wang, Naiyan Wang, Dit-Yan Yeung
2013 A* conf
Collaborative Topic Regression with Social Regularization for Tag Recommendation.
IJCAI
Hao Wang, Binyi Chen, Wu-Jun Li
2013 A* conf
Online Egocentric Models for Citation Networks.
IJCAI
Hao Wang, Wu-Jun Li