Haoxuan Li - RankMe

118 papers A* 47A 1Journal 64Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Analyzing and Improving Diffusion Models for Time-Series Data Imputation: A Proximal Recursion Perspective. CoRR Zhichao Chen, Hao Wang, Fangyikang Wang, Licheng Pan, Zhengnan Li, Yunfei Teng, Haoxuan Li, Zhouchen Lin
2026	J	`jnl`	Batch-Adaptive Doubly Robust Learning for Debiasing Post-Click Conversion Rate Prediction Under Sparse Data. ACM Trans. Inf. Syst. Hang Pan, Chunyuan Zheng, Wenjie Wang, Jingang Jiang, Xueying Li, Haoxuan Li, Fuli Feng
2026	J	`jnl`	Beyond Similarity: Personalized Federated Recommendation with Composite Aggregation. ACM Trans. Inf. Syst. Honglei Zhang, Haoxuan Li, Jundong Chen, Sen Cui, Kunda Yan, Abudukelimu Wuerkaixi, Xin Zhou, Zhiqi Shen, Yidong Li
2026	J	`jnl`	Causal Inference with Complex Treatments: A Survey. ACM Comput. Surv. Yingrong Wang, Haoxuan Li, Minqin Zhu, Anpeng Wu, Baohong Li, Keting Yin, Ruoxuan Xiong, Fei Wu, Kun Kuang
2026	J	`jnl`	CausalRM: Causal-Theoretic Reward Modeling for RLHF from Observational User Feedbacks. CoRR Hao Wang, Licheng Pan, Zhichao Chen, Chunyuan Zheng, Zhixuan Chu, Xiaoxi Li, Yuan Lu, Xinggao Liu, Haoxuan Li, Zhouchen Lin
2026	J	`jnl`	Deep Autocorrelation Modeling for Time-Series Forecasting: Progress and Prospects. CoRR 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
2026	J	`jnl`	Deep Time-series Forecasting Needs Kernelized Moment Balancing. CoRR Licheng Pan, Hao Wang, Haocheng Yang, Yuqi Li, Qingsong Wen, Xiaoxi Li, Zhichao Chen, Haoxuan Li, Zhixuan Chu, Yuan Lu
2026	J	`jnl`	ImplicitRM: Unbiased Reward Modeling from Implicit Preference Data for LLM alignment. CoRR Hao Wang, Haocheng Yang, Licheng Pan, Lei Shen, Xiaoxi Li, Yinuo Wang, Zhichao Chen, Yuan Lu, Haoxuan Li, Zhouchen Lin
2026	J	`jnl`	Invariant Causal Routing for Governing Social Norms in Online Market Economies. CoRR Xiangning Yu, Qirui Mi, Xiao Xue, Haoxuan Li, Yiwei Shi, Xiaowei Liu, Mengyue Yang
2026	J	`jnl`	Rethinking the Flow-Based Gradual Domain Adaption: A Semi-Dual Optimal Transport Perspective. CoRR Zhichao Chen, Zhan Zhuang, Yunfei Teng, Hao Wang, Fangyikang Wang, Zhengnan Li, Tianqiao Liu, Haoxuan Li, Zhouchen Lin
2026	A*	`conf`	TransFR: Transferable Federated Recommendation with Adapter Tuning on Pre-trained Language Models. AAAI Honglei Zhang, Zhiwei Li, Haoxuan Li, Xin Zhou, Jie Zhang, Yidong Li
2026	A*	`conf`	Uplift Modeling with Delayed Feedback: Identifiability and Algorithms. AAAI Chunyuan Zheng, Anpeng Wu, Chuan Zhou, Taojun Hu, Qingying Chen, Hongyi Liu, Chenxi Li, Huiyou Jiang, Haoxuan Li, Zhouchen Lin
2025	J	`jnl`	A Partial Initialization Strategy to Mitigate the Overfitting Problem in CATE Estimation with Hidden Confounding. CoRR Chuan Zhou, Yaxuan Li, Chunyuan Zheng, Haiteng Zhang, Haoxuan Li, Mingming Gong
2025	—	`conf`	A Two-Stage Pretraining-Finetuning Framework for Treatment Effect Estimation with Unmeasured Confounding. KDD (1) Chuan Zhou, Yaxuan Li, Chunyuan Zheng, Haiteng Zhang, Min Zhang, Haoxuan Li, Mingming Gong
2025	A*	`conf`	Active Treatment Effect Estimation via Limited Samples. ICML Zhiheng Zhang, Haoxiang Wang, Haoxuan Li, Zhouchen Lin
2025	A*	`conf`	Adaptive Structure Learning with Partial Parameter Sharing for Post-Click Conversion Rate Prediction. SIGIR Chunyuan Zheng, Hang Pan, Yang Zhang, Haoxuan Li
2025	J	`jnl`	Beyond Personalization: Federated Recommendation with Calibration via Low-rank Decomposition. CoRR Jundong Chen, Honglei Zhang, Haoxuan Li, Chunxu Zhang, Zhiwei Li, Yidong Li
2025	J	`jnl`	Breaking the Gradient Barrier: Unveiling Large Language Models for Strategic Classification. CoRR Xinpeng Lv, Yunxin Mao, Haoxuan Li, Ke Liang, Jinxuan Yang, Wanrong Huang, Haoang Chi, Huan Chen, Long Lan, Yuanlong Chen, Wenjing Yang, Haotian Wang
2025	A*	`conf`	CAP: Causal Air Quality Index Prediction Under Interference with Unmeasured Confounding. WWW Huayi Yang, Chunyuan Zheng, Guorui Liao, Shanshan Huang, Jun Liao, Zhili Gong, Haoxuan Li, Li Liu
2025	J	`jnl`	Causal Sufficiency and Necessity Improves Chain-of-Thought Reasoning. CoRR Xiangning Yu, Zhuohan Wang, Linyi Yang, Haoxuan Li, Anjie Liu, Xiao Xue, Jun Wang, Mengyue Yang
2025	—	`conf`	CharacterBox: Evaluating the Role-Playing Capabilities of LLMs in Text-Based Virtual Worlds. NAACL (Long Papers) Lei Wang, Jianxun Lian, Yi Huang, Yanqi Dai, Haoxuan Li, Xu Chen, Xing Xie, Ji-Rong Wen
2025	—	`conf`	Classifying Treatment Responders: Bounds and Algorithms. KDD (1) Anpeng Wu, Haoxuan Li, Chunyuan Zheng, Kun Kuang, Kun Zhang
2025	J	`jnl`	Curious Causality-Seeking Agents Learn Meta Causal World. CoRR Zhiyu Zhao, Haoxuan Li, Haifeng Zhang, Jun Wang, Francesco Faccio, Jürgen Schmidhuber, Mengyue Yang
2025	J	`jnl`	Debiased Recommendation via Wasserstein Causal Balancing. ACM Trans. Inf. Syst. Hao Wang, Zhichao Chen, Honglei Zhang, Zhengnan Li, Licheng Pan, Haoxuan Li, Mingming Gong
2025	J	`jnl`	Decentralized Dynamic Cooperation of Personalized Models for Federated Continual Learning. CoRR Danni Yang, Zhikang Chen, Sen Cui, Mengyue Yang, Ding Li, Abudukelimu Wuerkaixi, Haoxuan Li, Jinke Ren, Mingming Gong
2025	A*	`conf`	Decomposing and Fusing Intra- and Inter-Sensor Spatio-Temporal Signal for Multi-Sensor Wearable Human Activity Recognition. AAAI Haoyu Xie, Haoxuan Li, Chunyuan Zheng, Haonan Yuan, Guorui Liao, Jun Liao, Li Liu
2025	J	`jnl`	Decomposing and Fusing Intra- and Inter-Sensor Spatio-Temporal Signal for Multi-Sensor Wearable Human Activity Recognition. CoRR Haoyu Xie, Haoxuan Li, Chunyuan Zheng, Haonan Yuan, Guorui Liao, Jun Liao, Li Liu
2025	J	`jnl`	DistDF: Time-Series Forecasting Needs Joint-Distribution Wasserstein Alignment. CoRR Hao Wang, Licheng Pan, Yuan Lu, Zhixuan Chu, Xiaoxi Li, Shuting He, Zhichao Chen, Haoxuan Li, Qingsong Wen, Zhouchen Lin
2025	A*	`conf`	Effective and Efficient Time-Varying Counterfactual Prediction with State-Space Models. ICLR Haotian Wang, Haoxuan Li, Hao Zou, Haoang Chi, Long Lan, Wanrong Huang, Wenjing Yang
2025	A*	`conf`	Empowering LLMs with Logical Reasoning: A Comprehensive Survey. IJCAI Fengxiang Cheng, Haoxuan Li, Fenrong Liu, Robert van Rooij, Kun Zhang, Zhouchen Lin
2025	J	`jnl`	Empowering LLMs with Logical Reasoning: A Comprehensive Survey. CoRR Fengxiang Cheng, Haoxuan Li, Fenrong Liu, Robert van Rooij, Kun Zhang, Zhouchen Lin
2025	J	`jnl`	Entire Space Counterfactual Learning for Reliable Content Recommendations. IEEE Trans. Inf. Forensics Secur. Hao Wang, Zhichao Chen, Zhaoran Liu, Haozhe Li, Degui Yang, Xinggao Liu, Haoxuan Li
2025	J	`jnl`	Estimating the Effects of Sample Training Orders for Large Language Models without Retraining. CoRR Hao Yang, Haoxuan Li, Mengyue Yang, Xu Chen, Mingming Gong
2025	A*	`conf`	Fairness on Principal Stratum: A New Perspective on Counterfactual Fairness. ICML Haoxuan Li, Zeyu Tang, Zhichao Jiang, Zhuangyan Fang, Yue Liu, Zhi Geng, Kun Zhang
2025	A*	`conf`	FreDF: Learning to Forecast in the Frequency Domain. ICLR Hao Wang, Lichen Pan, Yuan Shen, Zhichao Chen, Degui Yang, Yifei Yang, Sen Zhang, Xinggao Liu, Haoxuan Li, Dacheng Tao
2025	A*	`conf`	HiPoser: 3D Human Pose Estimation with Hierarchical Shared Learning at Parts-Level Using Inertial Measurement Units. AAAI Guorui Liao, Chunyuan Zheng, Li Cheng, Haoyu Xie, Shanshan Huang, Jun Liao, Haoxuan Li, Li Liu
2025	A*	`conf`	Large Language Models are Demonstration Pre-Selectors for Themselves. ICML Jiarui Jin, Yuwei Wu, Haoxuan Li, Xiaoting He, Weinan Zhang, Yiming Yang, Yong Yu, Jun Wang, Mengyue Yang
2025	J	`jnl`	Large Language Models are Demonstration Pre-Selectors for Themselves. CoRR Jiarui Jin, Yuwei Wu, Haoxuan Li, Xiaoting He, Weinan Zhang, Yiming Yang, Yong Yu, Jun Wang, Mengyue Yang
2025	J	`jnl`	Learning Counterfactual Outcomes Under Rank Preservation. CoRR Peng Wu, Haoxuan Li, Chunyuan Zheng, Yan Zeng, Jiawei Chen, Yang Liu, Ruocheng Guo, Kun Zhang
2025	J	`jnl`	Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering. CoRR Tianjun Yao, Haoxuan Li, Zhiqiang Shen, Pan Li, Tongliang Liu, Kun Zhang
2025	J	`jnl`	Learning double balancing representation for heterogeneous dose-response curve estimation. Neural Networks Minqin Zhu, Anpeng Wu, Haoxuan Li, Ruoxuan Xiong, Bo Li, Fei Wu, Kun Kuang
2025	A*	`conf`	Learning without Isolation: Pathway Protection for Continual Learning. ICML Zhikang Chen, Abudukelimu Wuerkaixi, Sen Cui, Haoxuan Li, Ding Li, Jingfeng Zhang, Bo Han, Gang Niu, Houfang Liu, Yi Yang, Sifan Yang, Changshui Zhang, Tianling Ren
2025	J	`jnl`	Learning without Isolation: Pathway Protection for Continual Learning. CoRR Zhikang Chen, Abudukelimu Wuerkaixi, Sen Cui, Haoxuan Li, Ding Li, Jingfeng Zhang, Bo Han, Gang Niu, Houfang Liu, Yi Yang, Sifan Yang, Changshui Zhang, Tianling Ren
2025	J	`jnl`	MME-Emotion: A Holistic Evaluation Benchmark for Emotional Intelligence in Multimodal Large Language Models. CoRR Fan Zhang, Zebang Cheng, Chong Deng, Haoxuan Li, Zheng Lian, Qian Chen, Huadai Liu, Wen Wang, Yifan Zhang, Renrui Zhang, Ziyu Guo, Zhihong Zhu, Hao Wu, Haixin Wang, Yefeng Zheng, Xiaojiang Peng, Xian Wu, Kun Wang, Xiangang Li, Jieping Ye, Pheng-Ann Heng
2025	—	`conf`	Mitigating Data Imbalance in Time Series Classification Based on Counterfactual Minority Samples Augmentation. KDD (2) Lei Wang, Shanshan Huang, Chunyuan Zheng, Jun Liao, Xiaofei Zhu, Haoxuan Li, Li Liu
2025	J	`jnl`	Mitigating Hidden Confounding by Progressive Confounder Imputation via Large Language Models. CoRR Hao Yang, Haoxuan Li, Luyu Chen, Haoxiang Wang, Xu Chen, Mingming Gong
2025	—	`conf`	Mitigating Spurious Correlations via Counterfactual Contrastive Learning. EMNLP (Findings) Fengxiang Cheng, Chuan Zhou, Xiang Li, Alina Leidinger, Haoxuan Li, Mingming Gong, Fenrong Liu, Robert van Rooij
2025	J	`jnl`	Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting. CoRR Licheng Pan, Zhichao Chen, Haoxuan Li, Guangyi Liu, Zhijian Xu, Zhaoran Liu, Hao Wang, Ying Wei
2025	A*	`conf`	Optimal Transport for Time Series Imputation. ICLR Hao Wang, Zhengnan Li, Haoxuan Li, Xu Chen, Mingming Gong, BinChen, Zhichao Chen
2025	J	`jnl`	Proactive Recommendation in Social Networks: Steering user interest with causal inference. AI Open Hang Pan, Shuxian Bi, Wenjie Wang, Haoxuan Li, Peng Wu, Fuli Feng
2025	—	`conf`	Proximity Matters: Local Proximity Enhanced Balancing for Treatment Effect Estimation. KDD (2) Hao Wang, Zhichao Chen, Zhaoran Liu, Xu Chen, Haoxuan Li, Zhouchen Lin
2025	J	`jnl`	Pruning Spurious Subgraphs for Graph Out-of-Distribtuion Generalization. CoRR Tianjun Yao, Haoxuan Li, Yongqiang Chen, Tongliang Liu, Le Song, Eric P. Xing, Zhiqiang Shen
2025	J	`jnl`	Quadratic Direct Forecast for Training Multi-Step Time-Series Forecast Models. CoRR Hao Wang, Licheng Pan, Yuan Lu, Zhichao Chen, Tianqiao Liu, Shuting He, Zhixuan Chu, Qingsong Wen, Haoxuan Li, Zhouchen Lin
2025	J	`jnl`	Rethinking Facial Expression Recognition in the Era of Multimodal Large Language Models: Benchmark, Datasets, and Beyond. CoRR Fan Zhang, Haoxuan Li, Shengju Qian, Xin Wang, Zheng Lian, Hao Wu, Zhihong Zhu, Yuan Gao, Qiankun Li, Yefeng Zheng, Zhouchen Lin, Pheng-Ann Heng
2025	A*	`conf`	Text-Driven Fashion Image Editing with Compositional Concept Learning and Counterfactual Abduction. CVPR Shanshan Huang, Haoxuan Li, Chunyuan Zheng, Mingyuan Ge, Wei Gao, Lei Wang, Li Liu
2025	J	`jnl`	Towards Understanding Extrapolation: a Causal Lens. CoRR Lingjing Kong, Guangyi Chen, Petar Stojanov, Haoxuan Li, Eric P. Xing, Kun Zhang
2025	J	`jnl`	TransDF: Time-Series Forecasting Needs Transformed Label Alignment. CoRR Hao Wang, Licheng Pan, Zhichao Chen, Xu Chen, Qingyang Dai, Lei Wang, Haoxuan Li, Zhouchen Lin
2025	A*	`conf`	Unbiased Recommender Learning from Implicit Feedback via Weakly Supervised Learning. ICML Hao Wang, Zhichao Chen, Haotian Wang, Yanchao Tan, Pan Li, Tianqiao Liu, Xu Chen, Haoxuan Li, Zhouchen Lin
2025	A*	`conf`	Visual Representation Learning through Causal Intervention for Controllable Image Editing. CVPR Shanshan Huang, Haoxuan Li, Chunyuan Zheng, Lei Wang, Guorui Liao, Zhili Gong, Huayi Yang, Li Liu
2024	A*	`conf`	A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective. ICML Baohong Li, Haoxuan Li, Anpeng Wu, Minqin Zhu, Shiyuan Peng, Qingyu Cao, Kun Kuang
2024	J	`jnl`	Attaining Human's Desirable Outcomes in Human-AI Interaction via Structural Causal Games. CoRR Anjie Liu, Jianhong Wang, Haoxuan Li, Xu Chen, Jun Wang, Samuel Kaski, Mengyue Yang
2024	A*	`conf`	Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference. ICLR Haoxuan Li, Chunyuan Zheng, Sihao Ding, Peng Wu, Zhi Geng, Fuli Feng, Xiangnan He
2024	J	`jnl`	Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference. CoRR Haoxuan Li, Chunyuan Zheng, Sihao Ding, Peng Wu, Zhi Geng, Fuli Feng, Xiangnan He
2024	J	`jnl`	Beyond Similarity: Personalized Federated Recommendation with Composite Aggregation. CoRR Honglei Zhang, Haoxuan Li, Jundong Chen, Sen Cui, Kunda Yan, Abudukelimu Wuerkaixi, Xin Zhou, Zhiqi Shen, Yidong Li
2024	J	`jnl`	Causal Inference with Complex Treatments: A Survey. CoRR Yingrong Wang, Haoxuan Li, Minqin Zhu, Anpeng Wu, Ruoxuan Xiong, Fei Wu, Kun Kuang
2024	J	`jnl`	CharacterBox: Evaluating the Role-Playing Capabilities of LLMs in Text-Based Virtual Worlds. CoRR Lei Wang, Jianxun Lian, Yi Huang, Yanqi Dai, Haoxuan Li, Xu Chen, Xing Xie, Ji-Rong Wen
2024	A*	`conf`	Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation. AAAI Minqin Zhu, Anpeng Wu, Haoxuan Li, Ruoxuan Xiong, Bo Li, Xiaoqing Yang, Xuan Qin, Peng Zhen, Jiecheng Guo, Fei Wu, Kun Kuang
2024	J	`jnl`	Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation. CoRR Minqin Zhu, Anpeng Wu, Haoxuan Li, Ruoxuan Xiong, Bo Li, Xiaoqing Yang, Xuan Qin, Peng Zhen, Jiecheng Guo, Fei Wu, Kun Kuang
2024	J	`jnl`	CounterCLR: Counterfactual Contrastive Learning with Non-random Missing Data in Recommendation. CoRR Jun Wang, Haoxuan Li, Chi Zhang, Dongxu Liang, Enyun Yu, Wenwu Ou, Wenjia Wang
2024	A*	`conf`	Debiased Collaborative Filtering with Kernel-Based Causal Balancing. ICLR Haoxuan Li, Chunyuan Zheng, Yanghao Xiao, Peng Wu, Zhi Geng, Xu Chen, Peng Cui
2024	J	`jnl`	Debiased Collaborative Filtering with Kernel-Based Causal Balancing. CoRR Haoxuan Li, Chunyuan Zheng, Yanghao Xiao, Peng Wu, Zhi Geng, Xu Chen, Peng Cui
2024	A*	`conf`	Debiased Recommendation with Noisy Feedback. KDD Haoxuan Li, Chunyuan Zheng, Wenjie Wang, Hao Wang, Fuli Feng, Xiao-Hua Zhou
2024	J	`jnl`	Debiased Recommendation with Noisy Feedback. CoRR Haoxuan Li, Chunyuan Zheng, Wenjie Wang, Hao Wang, Fuli Feng, Xiao-Hua Zhou
2024	J	`jnl`	FSMLP: Modelling Channel Dependencies With Simplex Theory Based Multi-Layer Perceptions In Frequency Domain. CoRR Zhengnan Li, Haoxuan Li, Hao Wang, Jun Fang, Duoyin Li, Yunxiao Qin
2024	J	`jnl`	FreDF: Learning to Forecast in Frequency Domain. CoRR Hao Wang, Licheng Pan, Zhichao Chen, Degui Yang, Sen Zhang, Yifei Yang, Xinggao Liu, Haoxuan Li, Dacheng Tao
2024	A*	`conf`	Learning Causal Relations from Subsampled Time Series with Two Time-Slices. ICML Anpeng Wu, Haoxuan Li, Kun Kuang, Keli Zhang, Fei Wu
2024	A*	`conf`	Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias. ICML Baohong Li, Haoxuan Li, Ruoxuan Xiong, Anpeng Wu, Fei Wu, Kun Kuang
2024	A*	`conf`	MetaCoCo: A New Few-Shot Classification Benchmark with Spurious Correlation. ICLR Min Zhang, Haoxuan Li, Fei Wu, Kun Kuang
2024	J	`jnl`	MetaCoCo: A New Few-Shot Classification Benchmark with Spurious Correlation. CoRR Min Zhang, Haoxuan Li, Fei Wu, Kun Kuang
2024	A*	`conf`	Neural Collapse Inspired Feature Alignment for Out-of-Distribution Generalization. NeurIPS Zhikang Chen, Min Zhang, Sen Cui, Haoxuan Li, Gang Niu, Mingming Gong, Changshui Zhang, Kun Zhang
2024	A*	`conf`	On the Maximal Local Disparity of Fairness-Aware Classifiers. ICML Jinqiu Jin, Haoxuan Li, Fuli Feng
2024	J	`jnl`	On the Maximal Local Disparity of Fairness-Aware Classifiers. CoRR Jinqiu Jin, Haoxuan Li, Fuli Feng
2024	J	`jnl`	Pareto-Optimal Estimation and Policy Learning on Short-term and Long-term Treatment Effects. CoRR Yingrong Wang, Anpeng Wu, Haoxuan Li, Weiming Liu, Qiaowei Miao, Ruoxuan Xiong, Fei Wu, Kun Kuang
2024	J	`jnl`	Proactive Recommendation in Social Networks: Steering User Interest via Neighbor Influence. CoRR Hang Pan, Shuxian Bi, Wenjie Wang, Haoxuan Li, Peng Wu, Fuli Feng, Xiangnan He
2024	J	`jnl`	Proximity Matters: Local Proximity Preserved Balancing for Treatment Effect Estimation. CoRR Hao Wang, Zhichao Chen, Yuan Shen, Jiajun Fan, Zhaoran Liu, Degui Yang, Xinggao Liu, Haoxuan Li
2024	A*	`conf`	Relaxing the Accurate Imputation Assumption in Doubly Robust Learning for Debiased Collaborative Filtering. ICML Haoxuan Li, Chunyuan Zheng, Shuyi Wang, Kunhan Wu, Eric Hao Wang, Peng Wu, Zhi Geng, Xu Chen, Xiao-Hua Zhou
2024	A*	`conf`	Rethinking the Diffusion Models for Missing Data Imputation: A Gradient Flow Perspective. NeurIPS Zhichao Chen, Haoxuan Li, Fangyikang Wang, Odin Zhang, Hu Xu, Xiaoyu Jiang, Zhihuan Song, Hao Wang
2024	J	`jnl`	Rethinking the Diffusion Models for Numerical Tabular Data Imputation from the Perspective of Wasserstein Gradient Flow. CoRR Zhichao Chen, Haoxuan Li, Fangyikang Wang, Odin Zhang, Hu Xu, Xiaoyu Jiang, Zhihuan Song, Eric H. Wang
2024	A*	`conf`	Towards Understanding Extrapolation: a Causal Lens. NeurIPS Lingjing Kong, Guangyi Chen, Petar Stojanov, Haoxuan Li, Eric P. Xing, Kun Zhang
2024	J	`jnl`	TransFR: Transferable Federated Recommendation with Pre-trained Language Models. CoRR Honglei Zhang, He Liu, Haoxuan Li, Yidong Li
2024	A*	`conf`	Uncovering the Propensity Identification Problem in Debiased Recommendations. ICDE Honglei Zhang, Shuyi Wang, Haoxuan Li, Chunyuan Zheng, Xu Chen, Li Liu, Shanshan Luo, Peng Wu
2024	A*	`conf`	Your Neighbor Matters: Towards Fair Decisions Under Networked Interference. KDD Wenjing Yang, Haotian Wang, Haoxuan Li, Hao Zou, Ruochun Jin, Kun Kuang, Peng Cui
2023	A	`conf`	ADRNet: A Generalized Collaborative Filtering Framework Combining Clinical and Non-Clinical Data for Adverse Drug Reaction Prediction. RecSys Haoxuan Li, Taojun Hu, Zetong Xiong, Chunyuan Zheng, Fuli Feng, Xiangnan He, Xiao-Hua Zhou
2023	J	`jnl`	ADRNet: A Generalized Collaborative Filtering Framework Combining Clinical and Non-Clinical Data for Adverse Drug Reaction Prediction. CoRR Haoxuan Li, Taojun Hu, Zetong Xiong, Chunyuan Zheng, Fuli Feng, Xiangnan He, Xiao-Hua Zhou
2023	A*	`conf`	Balancing Unobserved Confounding with a Few Unbiased Ratings in Debiased Recommendations. WWW Haoxuan Li, Yanghao Xiao, Chunyuan Zheng, Peng Wu
2023	J	`jnl`	Balancing Unobserved Confounding with a Few Unbiased Ratings in Debiased Recommendations. CoRR Haoxuan Li, Yanghao Xiao, Chunyuan Zheng, Peng Wu
2023	A*	`conf`	Causal Recommendation: Progresses and Future Directions. SIGIR Wenjie Wang, Yang Zhang, Haoxuan Li, Peng Wu, Fuli Feng, Xiangnan He
2023	J	`jnl`	ConvFormer: Revisiting Transformer for Sequential User Modeling. CoRR Hao Wang, Jianxun Lian, Mingqi Wu, Haoxuan Li, Jiajun Fan, Wanyue Xu, Chaozhuo Li, Xing Xie
2023	A*	`conf`	CounterCLR: Counterfactual Contrastive Learning with Non-random Missing Data in Recommendation. ICDM Jun Wang, Haoxuan Li, Chi Zhang, Dongxu Liang, Enyun Yu, Wenwu Ou, Wenjia Wang
2023	A*	`conf`	Fairly Recommending with Social Attributes: A Flexible and Controllable Optimization Approach. NeurIPS Jinqiu Jin, Haoxuan Li, Fuli Feng, Sihao Ding, Peng Wu, Xiangnan He
2023	J	`jnl`	Hierarchical Topological Ordering with Conditional Independence Test for Limited Time Series. CoRR Anpeng Wu, Haoxuan Li, Kun Kuang, Keli Zhang, Fei Wu
2023	A*	`conf`	Multiple Robust Learning for Recommendation. AAAI Haoxuan Li, Quanyu Dai, Yuru Li, Yan Lyu, Zhenhua Dong, Xiao-Hua Zhou, Peng Wu
2023	A*	`conf`	Optimal Transport for Treatment Effect Estimation. NeurIPS Hao Wang, Jiajun Fan, Zhichao Chen, Haoxuan Li, Weiming Liu, Tianqiao Liu, Quanyu Dai, Yichao Wang, Zhenhua Dong, Ruiming Tang
2023	J	`jnl`	Optimal Transport for Treatment Effect Estimation. CoRR Hao Wang, Zhichao Chen, Jiajun Fan, Haoxuan Li, Tianqiao Liu, Weiming Liu, Quanyu Dai, Yichao Wang, Zhenhua Dong, Ruiming Tang
2023	A*	`conf`	Pareto Invariant Representation Learning for Multimedia Recommendation. ACM Multimedia Shanshan Huang, Haoxuan Li, Qingsong Li, Chunyuan Zheng, Li Liu
2023	J	`jnl`	Pareto Invariant Representation Learning for Multimedia Recommendation. CoRR Shanshan Huang, Haoxuan Li, Qingsong Li, Chunyuan Zheng, Li Liu
2023	A*	`conf`	Propensity Matters: Measuring and Enhancing Balancing for Recommendation. ICML Haoxuan Li, Yanghao Xiao, Chunyuan Zheng, Peng Wu, Peng Cui
2023	A*	`conf`	Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach. NeurIPS Haoxuan Li, Kunhan Wu, Chunyuan Zheng, Yanghao Xiao, Hao Wang, Zhi Geng, Fuli Feng, Xiangnan He, Peng Wu
2023	A*	`conf`	StableDR: Stabilized Doubly Robust Learning for Recommendation on Data Missing Not at Random. ICLR Haoxuan Li, Chunyuan Zheng, Peng Wu
2023	A*	`conf`	TDR-CL: Targeted Doubly Robust Collaborative Learning for Debiased Recommendations. ICLR Haoxuan Li, Yan Lyu, Chunyuan Zheng, Peng Wu
2023	A*	`conf`	Trustworthy Policy Learning under the Counterfactual No-Harm Criterion. ICML Haoxuan Li, Chunyuan Zheng, Yixiao Cao, Zhi Geng, Yue Liu, Peng Wu
2023	A*	`conf`	Who Should Be Given Incentives? Counterfactual Optimal Treatment Regimes Learning for Recommendation. KDD Haoxuan Li, Chunyuan Zheng, Peng Wu, Kun Kuang, Yue Liu, Peng Cui
2022	A*	`conf`	A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction. KDD Quanyu Dai, Haoxuan Li, Peng Wu, Zhenhua Dong, Xiao-Hua Zhou, Rui Zhang, Rui Zhang, Jie Sun
2022	J	`jnl`	A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction. CoRR Quanyu Dai, Haoxuan Li, Peng Wu, Zhenhua Dong, Xiao-Hua Zhou, Rui Zhang, Rui Zhang, Jie Sun
2022	J	`jnl`	Causal Analysis Framework for Recommendation. CoRR Peng Wu, Haoxuan Li, Yuhao Deng, Wenjie Hu, Quanyu Dai, Zhenhua Dong, Jie Sun, Rui Zhang, Xiao-Hua Zhou
2022	J	`jnl`	Doubly Robust Collaborative Targeted Learning for Recommendation on Data Missing Not at Random. CoRR Peng Wu, Haoxuan Li, Yan Lyu, Xiao-Hua Zhou
2022	A*	`conf`	On the Opportunity of Causal Learning in Recommendation Systems: Foundation, Estimation, Prediction and Challenges. IJCAI Peng Wu, Haoxuan Li, Yuhao Deng, Wenjie Hu, Quanyu Dai, Zhenhua Dong, Jie Sun, Rui Zhang, Xiao-Hua Zhou
2022	J	`jnl`	Stabilized Doubly Robust Learning for Recommendation on Data Missing Not at Random. CoRR Haoxuan Li, Chunyuan Zheng, Xiao-Hua Zhou, Peng Wu