Hao Wang

According to our database, Hao Wang authored at least 56 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

ImplicitRM: Unbiased Reward Modeling from Implicit Preference Data for LLM alignment.

Hao Wang, Haocheng Yang, Licheng Pan, Lei Shen, Xiaoxi Li, Yinuo Wang, Zhichao Chen, Yuan Lu, Haoxuan Li, Zhouchen Lin

CoRR, March, 2026

Deep Autocorrelation Modeling for Time-Series Forecasting: Progress and Prospects.

Hao Wang, Licheng Pan, Qingsong Wen, Jialin Yu, Zhichao Chen, Chunyuan Zheng, Xiaoxi Li, Zhixuan Chu, Chao Xu, Mingming Gong, Haoxuan Li, Yuan Lu, Zhouchen Lin, Philip Torr, Yan Liu

CoRR, March, 2026

CausalRM: Causal-Theoretic Reward Modeling for RLHF from Observational User Feedbacks.

Hao Wang, Licheng Pan, Zhichao Chen, Chunyuan Zheng, Zhixuan Chu, Xiaoxi Li, Yuan Lu, Xinggao Liu, Haoxuan Li, Zhouchen Lin

CoRR, March, 2026

Analyzing and Improving Diffusion Models for Time-Series Data Imputation: A Proximal Recursion Perspective.

Zhichao Chen, Hao Wang, Fangyikang Wang, Licheng Pan, Zhengnan Li, Yunfei Teng, Haoxuan Li, Zhouchen Lin

CoRR, February, 2026

Rethinking the Flow-Based Gradual Domain Adaption: A Semi-Dual Optimal Transport Perspective.

Zhichao Chen, Zhan Zhuang, Yunfei Teng, Hao Wang, Fangyikang Wang, Zhengnan Li, Tianqiao Liu, Haoxuan Li, Zhouchen Lin

CoRR, February, 2026

Deep Time-series Forecasting Needs Kernelized Moment Balancing.

Licheng Pan, Hao Wang, Haocheng Yang, Yuqi Li, Qingsong Wen, Xiaoxi Li, Zhichao Chen, Haoxuan Li, Zhixuan Chu, Yuan Lu

CoRR, February, 2026

Robust Missing Value Imputation With Proximal Optimal Transport for Low-Quality IIoT Data.

Hao Wang, Zhichao Chen, Yuan Shen, Hui Zheng, Degui Yang, Dangjun Zhao, Buge Liang

IEEE Trans. Neural Networks Learn. Syst., January, 2026

Blending Data and Knowledge for Process Industrial Modeling Under Riemannian Preconditioned Bayesian Framework.

Zhichao Chen, Yulong Zhang, Odin Zhang, Fangyikang Wang, Le Yao, Hao Wang, Zhihuan Song

IEEE Trans. Knowl. Data Eng., January, 2026

DeepAgent: A General Reasoning Agent with Scalable Toolsets.

Xiaoxi Li, Wenxiang Jiao, Jiarui Jin, Guanting Dong, Jiajie Jin, Yinuo Wang, Hao Wang, Yutao Zhu, Ji-Rong Wen, Yuan Lu, Zhicheng Dou

Proceedings of the ACM Web Conference 2026, 2026

2025

The Procrustean Bed of Time Series: The Optimization Bias of Point-wise Loss.

Rongyao Cai, Yuxi Wan, Kexin Zhang, Ming Jin, Hao Wang, Zhiqiang Ge, Daoyi Dong, Yong Li, Qingsong Wen

CoRR, December, 2025

Debiased Recommendation via Wasserstein Causal Balancing.

Hao Wang, Zhichao Chen, Honglei Zhang, Zhengnan Li, Licheng Pan, Haoxuan Li, Mingming Gong

ACM Trans. Inf. Syst., November, 2025

Quadratic Direct Forecast for Training Multi-Step Time-Series Forecast Models.

Hao Wang, Licheng Pan, Yuan Lu, Zhichao Chen, Tianqiao Liu, Shuting He, Zhixuan Chu, Qingsong Wen, Haoxuan Li, Zhouchen Lin

CoRR, November, 2025

DistDF: Time-Series Forecasting Needs Joint-Distribution Wasserstein Alignment.

Hao Wang, Licheng Pan, Yuan Lu, Zhixuan Chu, Xiaoxi Li, Shuting He, Zhichao Chen, Haoxuan Li, Qingsong Wen, Zhouchen Lin

CoRR, October, 2025

From Text to Talk: Audio-Language Model Needs Non-Autoregressive Joint Training.

Tianqiao Liu, Xueyi Li, Hao Wang, Haoxuan Li, Zhichao Chen, Weiqi Luo, Zitao Liu

CoRR, September, 2025

Relaxing Probabilistic Latent Variable Models' Specification via Infinite-Horizon Optimal Control.

Zhichao Chen, Hao Wang, Licheng Pan, Yiran Ma, Yunfei Teng, Jiaze Ma, Le Yao, Zhiqiang Ge, Zhihuan Song

CoRR, July, 2025

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting.

Licheng Pan, Zhichao Chen, Haoxuan Li, Guangyi Liu, Zhijian Xu, Zhaoran Liu, Hao Wang, Ying Wei

CoRR, May, 2025

TransDF: Time-Series Forecasting Needs Transformed Label Alignment.

Hao Wang, Licheng Pan, Zhichao Chen, Xu Chen, Qingyang Dai, Lei Wang, Haoxuan Li, Zhouchen Lin

CoRR, May, 2025

Improving Data-Driven Inferential Sensor Modeling by Industrial Knowledge: A Bayesian Perspective.

Zhichao Chen, Hao Wang, Zhihuan Song, Zhiqiang Ge

IEEE Trans. Syst. Man Cybern. Syst., February, 2025

DeepFilter: An Instrumental Baseline for Accurate and Efficient Process Monitoring.

Hao Wang, Zhichao Chen, Licheng Pan, Xiaoyu Jiang, Yichen Song, Qunshan He, Xinggao Liu

CoRR, January, 2025

Entire Space Counterfactual Learning for Reliable Content Recommendations.

Hao Wang, Zhichao Chen, Zhaoran Liu, Haozhe Li, Degui Yang, Xinggao Liu, Haoxuan Li

IEEE Trans. Inf. Forensics Secur., 2025

LSPT-D: Local Similarity Preserved Transport for Direct Industrial Data Imputation.

Hao Wang, Xinggao Liu, Zhaoran Liu, Haozhe Li, Yilin Liao, Yuxin Huang, Zhichao Chen

IEEE Trans Autom. Sci. Eng., 2025

Controllable Mixture-of-Experts for Multivariate Soft Sensors.

Licheng Pan, Hao Wang, Zhichao Chen, Yuxin Huang, Yunlong Niu, Zhaoran Liu, Qunshan He, Xinggao Liu

IEEE Trans Autom. Sci. Eng., 2025

TMoE-P: Toward the Pareto Optimum for Multivariate Soft Sensors.

Licheng Pan, Hao Wang, Zhichao Chen, Yuxin Huang, Zhaoran Liu, Qunshan He, Xinggao Liu

IEEE Trans Autom. Sci. Eng., 2025

Proximity Matters: Local Proximity Enhanced Balancing for Treatment Effect Estimation.

Hao Wang, Zhichao Chen, Zhaoran Liu, Xu Chen, Haoxuan Li, Zhouchen Lin

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

Unbiased Recommender Learning from Implicit Feedback via Weakly Supervised Learning.

Hao Wang, Zhichao Chen, Haotian Wang, Yanchao Tan, Pan Li, Tianqiao Liu, Xu Chen, Haoxuan Li, Zhouchen Lin

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Optimal Transport for Time Series Imputation.

Hao Wang, Zhengnan Li, Haoxuan Li, Xu Chen, Mingming Gong, BinChen, Zhichao Chen

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

FreDF: Learning to Forecast in the Frequency Domain.

Hao Wang, Lichen Pan, Yuan Shen, Zhichao Chen, Degui Yang, Yifei Yang, Sen Zhang, Xinggao Liu, Haoxuan Li, Dacheng Tao

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

SPOT-I: Similarity Preserved Optimal Transport for Industrial IoT Data Imputation.

Hao Wang, Zhichao Chen, Zhaoran Liu, Licheng Pan, Hu Xu, Yilin Liao, Haozhe Li, Xinggao Liu

IEEE Trans. Ind. Informatics, December, 2024

Analyzing and Improving Supervised Nonlinear Dynamical Probabilistic Latent Variable Model for Inferential Sensors.

Zhichao Chen, Hao Wang, Guofei Chen, Yiran Ma, Le Yao, Zhiqiang Ge, Zhihuan Song

IEEE Trans. Ind. Informatics, November, 2024

Denoising Diffusion Straightforward Models for Energy Conversion Monitoring Data Imputation.

Hu Xu, Zhaoran Liu, Hao Wang, Changdi Li, Yunlong Niu, Wenhai Wang, Xinggao Liu

IEEE Trans. Ind. Informatics, October, 2024

An Accurate and Interpretable Framework for Trustworthy Process Monitoring.

Hao Wang, Zhiyu Wang, Yunlong Niu, Zhaoran Liu, Haozhe Li, Yilin Liao, Yuxin Huang, Xinggao Liu

IEEE Trans. Artif. Intell., May, 2024

Integrating regular expressions into neural networks for relation extraction.

Zhaoran Liu, Xinjie Chen, Hao Wang, Xinggao Liu

Expert Syst. Appl., 2024

FSMLP: Modelling Channel Dependencies With Simplex Theory Based Multi-Layer Perceptions In Frequency Domain.

Zhengnan Li, Haoxuan Li, Hao Wang, Jun Fang, Duoyin Li, Yunxiao Qin

CoRR, 2024

Proximity Matters: Local Proximity Preserved Balancing for Treatment Effect Estimation.

Hao Wang, Zhichao Chen, Yuan Shen, Jiajun Fan, Zhaoran Liu, Degui Yang, Xinggao Liu, Haoxuan Li

CoRR, 2024

FreDF: Learning to Forecast in Frequency Domain.

Hao Wang, Licheng Pan, Zhichao Chen, Degui Yang, Sen Zhang, Yifei Yang, Xinggao Liu, Haoxuan Li, Dacheng Tao

CoRR, 2024

A Data-Centric Multi-Objective Learning Framework for Responsible Recommendation Systems.

Xu Huang, Jianxun Lian, Hao Wang, Hao Liao, Defu Lian, Xing Xie

Proceedings of the ACM on Web Conference 2024, 2024

Rethinking the Diffusion Models for Missing Data Imputation: A Gradient Flow Perspective.

Zhichao Chen, Haoxuan Li, Fangyikang Wang, Odin Zhang, Hu Xu, Xiaoyu Jiang, Zhihuan Song, Hao Wang

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Debiased Recommendation with Noisy Feedback.

Haoxuan Li, Chunyuan Zheng, Wenjie Wang, Hao Wang, Fuli Feng, Xiao-Hua Zhou

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Relaxing the Accurate Imputation Assumption in Doubly Robust Learning for Debiased Collaborative Filtering.

Haoxuan Li, Chunyuan Zheng, Shuyi Wang, Kunhan Wu, Eric Hao Wang, Peng Wu, Zhi Geng, Xu Chen, Xiao-Hua Zhou

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Improving Neural Network Generalization on Data-Limited Regression with Doubly-Robust Boosting.

Hao Wang

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

A novel pipelined end-to-end relation extraction framework with entity mentions and contextual semantic representation.

Zhaoran Liu, Haozhe Li, Hao Wang, Yilin Liao, Xinggao Liu, Gaojie Wu

Expert Syst. Appl., October, 2023

Modeling Task Relationships in Multivariate Soft Sensor With Balanced Mixture-of-Experts.

Yuxin Huang, Eric Hao Wang, Zhaoran Liu, Licheng Pan, Haozhe Li, Xinggao Liu

IEEE Trans. Ind. Informatics, May, 2023

Omnidirectional Image Super-Resolution via Latitude Adaptive Network.

Xin Deng, Hao Wang, Mai Xu, Li Li, Zulin Wang

IEEE Trans. Multim., 2023

A Data-Centric Multi-Objective Learning Framework for Responsible Recommendation Systems.

Xu Huang, Jianxun Lian, Hao Wang, Defu Lian, Xing Xie

CoRR, 2023

ConvFormer: Revisiting Transformer for Sequential User Modeling.

Hao Wang, Jianxun Lian, Mingqi Wu, Haoxuan Li, Jiajun Fan, Wanyue Xu, Chaozhuo Li, Xing Xie

CoRR, 2023

TMoE-P: Towards the Pareto Optimum for Multivariate Soft Sensors.

Licheng Pan, Hao Wang, Zhichao Chen, Yuxing Huang, Xinggao Liu

CoRR, 2023

Optimal Transport for Treatment Effect Estimation.

Hao Wang, Jiajun Fan, Zhichao Chen, Haoxuan Li, Weiming Liu, Tianqiao Liu, Quanyu Dai, Yichao Wang, Zhenhua Dong, Ruiming Tang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach.

Haoxuan Li, Kunhan Wu, Chunyuan Zheng, Yanghao Xiao, Hao Wang, Zhi Geng, Fuli Feng, Xiangnan He, Peng Wu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learnable Behavior Control: Breaking Atari Human World Records via Sample-Efficient Behavior Selection.

Jiajun Fan, Yuzheng Zhuang, Yuecheng Liu, Jianye Hao, Bin Wang, Jiangcheng Zhu, Hao Wang, Shu-Tao Xia

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Unsupervised Anomaly Detection & Diagnosis: A Stein Variational Gradient Descent Approach.

Zhichao Chen, Leilei Ding, Jianmin Huang, Zhixuan Chu, Qingyang Dai, Hao Wang

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Monotonic Neural Ordinary Differential Equation: Time-series Forecasting for Cumulative Data.

Zhichao Chen, Leilei Ding, Zhixuan Chu, Yucheng Qi, Jianmin Huang, Hao Wang

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

Entire Space Counterfactual Learning: Tuning, Analytical Properties and Industrial Applications.

Hao Wang, Zhichao Chen, Jiajun Fan, Yuxin Huang, Weiming Liu, Xinggao Liu

CoRR, 2022

ESCM²: Entire Space Counterfactual Multi-Task Model for Post-Click Conversion Rate Estimation.

Hao Wang, Tai-Wei Chang, Tianqiao Liu, Jianmin Huang, Zhichao Chen, Chao Yu, Ruopeng Li, Wei Chu

CoRR, 2022

ESCM2: Entire Space Counterfactual Multi-Task Model for Post-Click Conversion Rate Estimation.

Hao Wang, Tai-Wei Chang, Tianqiao Liu, Jianmin Huang, Zhichao Chen, Chao Yu, Ruopeng Li, Wei Chu

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

2021

LAU-Net: Latitude Adaptive Upscaling Network for Omnidirectional Image Super-Resolution.

Xin Deng, Hao Wang, Mai Xu, Yichen Guo, Yuhang Song, Li Yang

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

A Meta-Learning Framework for Learning Multi-User Preferences in QoE Optimization of DASH.

Liangyu Huo, Zulin Wang, Mai Xu, Yong Li, Zhiguo Ding, Hao Wang

IEEE Trans. Circuits Syst. Video Technol., 2020