default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDKun Kuang
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2025
[j35]Tianqianjin Lin
, Yangyang Kang, Zhuoren Jiang, Kaisong Song, Kun Kuang, Changlong Sun, Cui Huang, Xiaozhong Liu:
Unraveling and Mitigating Endogenous Task-oriented Spurious Correlations in Ego-graphs via Automated Counterfactual Contrastive Learning. Expert Syst. Appl. 266: 126015 (2025)- [j34]Ziyu Zhao, Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Bo Li, Zhihua Wang, Fei Wu:
Networked Instrumental Variable for Treatment Effect Estimation With Unobserved Confounders. IEEE Trans. Knowl. Data Eng. 37(2): 823-836 (2025) - [c112]Yinghao Hu, Leilei Gan, Wenyi Xiao, Kun Kuang, Fei Wu:
Fine-tuning Large Language Models for Improving Factuality in Legal Question Answering. COLING 2025: 4410-4427 - [i100]Jianfeng Xu, Congcong Liu, Xiaoying Tan, Xiaojie Zhu, Anpeng Wu, Huan Wan, Weijun Kong, Chun Li, Hu Xu, Kun Kuang, Fei Wu:
General Information Metrics for Improving AI Model Training Efficiency. CoRR abs/2501.02004 (2025) - [i99]Kairui Fu, Zheqi Lv, Shengyu Zhang, Fan Wu, Kun Kuang:
Forward Once for All: Structural Parameterized Adaptation for Efficient Cloud-coordinated On-device Recommendation. CoRR abs/2501.02837 (2025) - [i98]Zheqi Lv, Tianyu Zhan, Wenjie Wang, Xinyu Lin, Shengyu Zhang, Wenqiao Zhang, Jiwei Li, Kun Kuang, Fei Wu:
Collaboration of Large Language Models and Small Recommendation Models for Device-Cloud Recommendation. CoRR abs/2501.05647 (2025) - [i97]Yinghao Hu, Leilei Gan, Wenyi Xiao, Kun Kuang, Fei Wu:
Fine-tuning Large Language Models for Improving Factuality in Legal Question Answering. CoRR abs/2501.06521 (2025) - 2024
- [j33]Xiang Zhou, Qi Liu, Yiquan Wu, Qiangchao Chen, Kun Kuang:
LK-IB: a hybrid framework with legal knowledge injection for compulsory measure prediction. Artif. Intell. Law 32(3): 595-620 (2024) - [j32]Ziyu Zhao, Leilei Gan, Tao Shen, Kun Kuang, Fei Wu:
Deconfounded hierarchical multi-granularity classification. Comput. Vis. Image Underst. 248: 104108 (2024) - [j31]Xiang Zhou, Yudong Wu, Ang Li, Ming Cai, Yiquan Wu, Kun Kuang:
Unlocking authentic judicial reasoning: A Template-Based Legal Information Generation framework for judicial views. Knowl. Based Syst. 301: 112232 (2024) - [j30]Danyang Gao, Ming Kong, Yongrui Zhao, Jing Huang, Zhengxing Huang, Kun Kuang, Fei Wu, Qiang Zhu:
Simulating doctors' thinking logic for chest X-ray report generation via Transformer-based Semantic Query learning. Medical Image Anal. 91: 102982 (2024) - [j29]Fengda Zhang, Zitao Shuai, Kun Kuang, Fei Wu, Yueting Zhuang, Jun Xiao:
Unified fair federated learning for digital healthcare. Patterns 5(1): 100907 (2024) - [j28]Shuting Shi, Baohong Li, Laifu Zhang, Kun Kuang, Sensen Wu, Tian Feng, Yiming Yan, Zhenhong Du:
Causality-Guided Stepwise Intervention and Reweighting for Remote Sensing Image Semantic Segmentation. IEEE Trans. Geosci. Remote. Sens. 62: 1-17 (2024) - [j27]Ziyu Zhao, Yuqi Bai, Ruoxuan Xiong, Qingyu Cao, Chao Ma, Ning Jiang, Fei Wu, Kun Kuang:
Learning Individual Treatment Effects under Heterogeneous Interference in Networks. ACM Trans. Knowl. Discov. Data 18(8): 199:1-199:21 (2024) - [j26]Shengyu Zhang, Ziqi Jiang, Jiangchao Yao, Fuli Feng, Kun Kuang, Zhou Zhao, Shuo Li, Hongxia Yang, Tat-Seng Chua, Fei Wu:
Causal Distillation for Alleviating Performance Heterogeneity in Recommender Systems. IEEE Trans. Knowl. Data Eng. 36(2): 459-474 (2024) - [j25]Haotian Wang, Kun Kuang, Long Lan, Zige Wang, Wanrong Huang, Fei Wu, Wenjing Yang:
Out-of-Distribution Generalization With Causal Feature Separation. IEEE Trans. Knowl. Data Eng. 36(4): 1758-1772 (2024) - [j24]Jiannan Guo, Yangyang Kang, Xiaolin Li, Wenqiao Zhang, Kun Kuang, Changlong Sun, Siliang Tang, Fei Wu:
Unleash the Power of Inconsistency-Based Semi-Supervised Active Learning by Dynamic Programming of Curriculum Learning. IEEE Trans. Knowl. Data Eng. 36(11): 7268-7282 (2024) - [j23]Shaohua Fan, Xiao Wang, Chuan Shi, Kun Kuang, Nian Liu, Bai Wang:
Debiased Graph Neural Networks With Agnostic Label Selection Bias. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4411-4422 (2024) - [j22]Shengyu Zhang, Tan Jiang, Kun Kuang, Fuli Feng, Jin Yu, Jianxin Ma, Zhou Zhao, Jianke Zhu, Hongxia Yang, Tat-Seng Chua, Fei Wu:
SLED: Structure Learning based Denoising for Recommendation. ACM Trans. Inf. Syst. 42(2): 43:1-43:31 (2024) - [j21]Shengyu Zhang, Qiaowei Miao, Ping Nie, Mengze Li, Zhengyu Chen, Fuli Feng, Kun Kuang, Fei Wu:
Transferring Causal Mechanism over Meta-representations for Target-Unknown Cross-domain Recommendation. ACM Trans. Inf. Syst. 42(4): 103:1-103:27 (2024) - [c111]Junao Shen, Kun Kuang, Jiaheng Wang, Xinyu Wang, Tian Feng, Wei Zhang:
CGMGM: A Cross-Gaussian Mixture Generative Model for Few-Shot Semantic Segmentation. AAAI 2024: 4784-4792 - [c110]Zhengyu Chen, Teng Xiao, Kun Kuang, Zheqi Lv, Min Zhang, Jinluan Yang, Chengqiang Lu, Hongxia Yang, Fei Wu:
Learning to Reweight for Generalizable Graph Neural Network. AAAI 2024: 8320-8328 - [c109]Kexin Li, Chengjiang Long, Shengyu Zhang, Xudong Tang, Zhichao Zhai, Kun Kuang, Jun Xiao:
CoreRec: A Counterfactual Correlation Inference for Next Set Recommendation. AAAI 2024: 8661-8669 - [c108]Minqin Zhu, Anpeng Wu, Haoxuan Li, Ruoxuan Xiong, Bo Li, Xiaoqing Yang, Xuan Qin, Peng Zhen, Jiecheng Guo, Fei Wu, Kun Kuang:
Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation. AAAI 2024: 17175-17183 - [c107]Yiquan Wu, Yifei Liu, Ziyu Zhao, Weiming Lu, Yating Zhang, Changlong Sun, Fei Wu, Kun Kuang:
De-biased Attention Supervision for Text Classification with Causality. AAAI 2024: 19279-19287 - [c106]Ziyu Zhao, Leilei Gan, Guoyin Wang, Wangchunshu Zhou, Hongxia Yang, Kun Kuang, Fei Wu:
LoraRetriever: Input-Aware LoRA Retrieval and Composition for Mixed Tasks in the Wild. ACL (Findings) 2024: 4447-4462 - [c105]Anlai Zhou, Sunshine Jiang, Yifei Liu, Yiquan Wu, Kun Kuang, Jun Xiao:
Latent Learningscape Guided In-context Learning. ACL (Findings) 2024: 8090-8101 - [c104]Yiquan Wu, Anlai Zhou, Yuhang Liu, Yifei Liu, Adam Jatowt, Weiming Lu, Jun Xiao, Kun Kuang:
Chain-of-Quizzes: Pedagogy-inspired Example Selection in In-Context-Learning. ACL (Findings) 2024: 10136-10142 - [c103]Ang Li, Yiquan Wu, Yifei Liu, Kun Kuang, Fei Wu, Ming Cai:
Enhancing Court View Generation with Knowledge Injection and Guidance. LREC/COLING 2024: 5896-5906 - [c102]Chengyuan Liu, Fubang Zhao, Kun Kuang, Yangyang Kang, Zhuoren Jiang, Changlong Sun, Fei Wu:
Evolving Knowledge Distillation with Large Language Models and Active Learning. LREC/COLING 2024: 6717-6731 - [c101]Ang Li, Qiangchao Chen, Yiquan Wu, Xiang Zhou, Kun Kuang, Fei Wu, Ming Cai:
From Graph to Word Bag: Introducing Domain Knowledge to Confusing Charge Prediction. LREC/COLING 2024: 7469-7479 - [c100]Fengda Zhang, Qianpei He, Kun Kuang, Jiashuo Liu, Long Chen, Chao Wu, Jun Xiao, Hanwang Zhang:
Distributionally Generative Augmentation for Fair Facial Attribute Classification. CVPR 2024: 22797-22808 - [c99]Chengyuan Liu, Shihang Wang, Lizhi Qing, Kun Kuang, Yangyang Kang, Changlong Sun, Fei Wu:
Gold Panning in Vocabulary: An Adaptive Method for Vocabulary Expansion of Domain-Specific LLMs. EMNLP 2024: 7442-7459 - [c98]Chengyuan Liu, Yangyang Kang, Shihang Wang, Lizhi Qing, Fubang Zhao, Chao Wu, Changlong Sun, Kun Kuang, Fei Wu:
More Than Catastrophic Forgetting: Integrating General Capabilities For Domain-Specific LLMs. EMNLP 2024: 7531-7548 - [c97]Jiahui Li, Hanlin Zhang, Fengda Zhang, Tai-Wei Chang, Kun Kuang, Long Chen, Jun Zhou:
Optimizing Language Models with Fair and Stable Reward Composition in Reinforcement Learning. EMNLP 2024: 10122-10140 - [c96]Qiaowei Miao, Junkun Yuan, Shengyu Zhang, Fei Wu, Kun Kuang:
Domaindiff: Boost out-of-Distribution Generalization with Synthetic Data. ICASSP 2024: 5640-5644 - [c95]Yuling Zhang, Anpeng Wu, Kun Kuang, Liang Du, Zixun Sun, Zhi Wang:
Stable Heterogeneous Treatment Effect Estimation across Out-of-Distribution Populations. ICDE 2024: 1117-1130 - [c94]Zihao Tang, Zheqi Lv, Shengyu Zhang, Yifan Zhou, Xinyu Duan, Fei Wu, Kun Kuang:
AuG-KD: Anchor-Based Mixup Generation for Out-of-Domain Knowledge Distillation. ICLR 2024 - [c93]Min Zhang, Haoxuan Li, Fei Wu, Kun Kuang:
MetaCoCo: A New Few-Shot Classification Benchmark with Spurious Correlation. ICLR 2024 - [c92]Xueyu Hu, Ziyu Zhao, Shuang Wei, Ziwei Chai, Qianli Ma, Guoyin Wang, Xuwu Wang, Jing Su, Jingjing Xu, Ming Zhu, Yao Cheng, Jianbo Yuan, Jiwei Li, Kun Kuang, Yang Yang, Hongxia Yang, Fei Wu:
InfiAgent-DABench: Evaluating Agents on Data Analysis Tasks. ICML 2024 - [c91]Baohong Li, Haoxuan Li, Anpeng Wu, Minqin Zhu, Shiyuan Peng, Qingyu Cao, Kun Kuang:
A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective. ICML 2024 - [c90]Baohong Li, Haoxuan Li, Ruoxuan Xiong, Anpeng Wu, Fei Wu, Kun Kuang:
Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias. ICML 2024 - [c89]Baohong Li, Anpeng Wu, Ruoxuan Xiong, Kun Kuang:
Two-Stage Shadow Inclusion Estimation: An IV Approach for Causal Inference under Latent Confounding and Collider Bias. ICML 2024 - [c88]Anpeng Wu, Haoxuan Li, Kun Kuang, Keli Zhang, Fei Wu:
Learning Causal Relations from Subsampled Time Series with Two Time-Slices. ICML 2024 - [c87]Didi Zhu, Zhongyi Sun, Zexi Li, Tao Shen, Ke Yan, Shouhong Ding, Chao Wu, Kun Kuang:
Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models. ICML 2024 - [c86]Wenjing Yang, Haotian Wang, Haoxuan Li, Hao Zou, Ruochun Jin, Kun Kuang, Peng Cui:
Your Neighbor Matters: Towards Fair Decisions Under Networked Interference. KDD 2024: 3829-3840 - [c85]Didi Zhu, Zexi Li, Min Zhang, Junkun Yuan, Jiashuo Liu, Kun Kuang, Chao Wu:
Neural Collapse Anchored Prompt Tuning for Generalizable Vision-Language Models. KDD 2024: 4631-4640 - [c84]Yiquan Wu, Bo Tang, Chenyang Xi, Yu Yu, Pengyu Wang, Yifei Liu, Kun Kuang, Haiying Deng, Zhiyu Li, Feiyu Xiong, Jie Hu, Peng Cheng, Zhonghao Wang, Yi Wang, Yi Luo, Mingchuan Yang:
Xinyu: An Efficient LLM-based System for Commentary Generation. KDD 2024: 6003-6014 - [c83]Tao Wu, Mengze Li, Jingyuan Chen, Wei Ji, Wang Lin, Jinyang Gao, Kun Kuang, Zhou Zhao, Fei Wu:
Semantic Alignment for Multimodal Large Language Models. ACM Multimedia 2024: 3489-3498 - [c82]Yifei Liu, Yiquan Wu, Ang Li, Yating Zhang, Changlong Sun, Weiming Lu, Fei Wu, Kun Kuang:
Unleashing the Power of LLMs in Court View Generation by Stimulating Internal Knowledge and Incorporating External Knowledge. NAACL-HLT (Findings) 2024: 2782-2792 - [c81]Zheqi Lv, Wenqiao Zhang, Zhengyu Chen, Shengyu Zhang, Kun Kuang:
Intelligent Model Update Strategy for Sequential Recommendation. WWW 2024: 3117-3128 - [i96]Xueyu Hu, Kun Kuang, Jiankai Sun, Hongxia Yang, Fei Wu:
Leveraging Print Debugging to Improve Code Generation in Large Language Models. CoRR abs/2401.05319 (2024) - [i95]Xueyu Hu, Ziyu Zhao, Shuang Wei, Ziwei Chai, Guoyin Wang, Xuwu Wang, Jing Su, Jingjing Xu, Ming Zhu, Yao Cheng, Jianbo Yuan, Kun Kuang, Yang Yang, Hongxia Yang, Fei Wu:
InfiAgent-DABench: Evaluating Agents on Data Analysis Tasks. CoRR abs/2401.05507 (2024) - [i94]Zhengqing Fang, Shuowen Zhou, Zhouhang Yuan, Yuxuan Si, Mengze Li, Jinxu Li, Yesheng Xu, Wenjia Xie, Kun Kuang, Yingming Li, Fei Wu, Yu-Feng Yao:
Enabling Collaborative Clinical Diagnosis of Infectious Keratitis by Integrating Expert Knowledge and Interpretable Data-driven Intelligence. CoRR abs/2401.08695 (2024) - [i93]Ziyu Zhao, Leilei Gan, Guoyin Wang, Wangchunshu Zhou, Hongxia Yang, Kun Kuang, Fei Wu:
LoraRetriever: Input-Aware LoRA Retrieval and Composition for Mixed Tasks in the Wild. CoRR abs/2402.09997 (2024) - [i92]Didi Zhu, Zhongyi Sun, Zexi Li, Tao Shen, Ke Yan, Shouhong Ding, Kun Kuang, Chao Wu:
Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models. CoRR abs/2402.12048 (2024) - [i91]Zihao Tang, Zheqi Lv, Shengyu Zhang, Fei Wu, Kun Kuang:
ModelGPT: Unleashing LLM's Capabilities for Tailored Model Generation. CoRR abs/2402.12408 (2024) - [i90]Yingrong Wang, Anpeng Wu, Haoxuan Li, Weiming Liu, Qiaowei Miao, Ruoxuan Xiong, Fei Wu, Kun Kuang:
Pareto-Optimal Estimation and Policy Learning on Short-term and Long-term Treatment Effects. CoRR abs/2403.02624 (2024) - [i89]Ang Li, Yiquan Wu, Yifei Liu, Fei Wu, Ming Cai, Kun Kuang:
Enhancing Court View Generation with Knowledge Injection and Guidance. CoRR abs/2403.04366 (2024) - [i88]Ang Li, Qiangchao Chen, Yiquan Wu, Ming Cai, Xiang Zhou, Fei Wu, Kun Kuang:
From Graph to Word Bag: Introducing Domain Knowledge to Confusing Charge Prediction. CoRR abs/2403.04369 (2024) - [i87]Chengyuan Liu, Yangyang Kang, Fubang Zhao, Kun Kuang, Zhuoren Jiang, Changlong Sun, Fei Wu:
Evolving Knowledge Distillation with Large Language Models and Active Learning. CoRR abs/2403.06414 (2024) - [i86]Dingyuan Zhu, Daixin Wang, Zhiqiang Zhang, Kun Kuang, Yan Zhang, Yulin Kang, Jun Zhou:
Graph Neural Network with Two Uplift Estimators for Label-Scarcity Individual Uplift Modeling. CoRR abs/2403.06489 (2024) - [i85]Fengda Zhang, Qianpei He, Kun Kuang, Jiashuo Liu, Long Chen, Chao Wu, Jun Xiao, Hanwang Zhang:
Distributionally Generative Augmentation for Fair Facial Attribute Classification. CoRR abs/2403.06606 (2024) - [i84]Zihao Tang, Zheqi Lv, Shengyu Zhang, Yifan Zhou, Xinyu Duan, Fei Wu, Kun Kuang:
AuG-KD: Anchor-Based Mixup Generation for Out-of-Domain Knowledge Distillation. CoRR abs/2403.07030 (2024) - [i83]Ruihao Zhang, Zhengyu Chen, Teng Xiao, Yueyang Wang, Kun Kuang:
Discovering Invariant Neighborhood Patterns for Heterophilic Graphs. CoRR abs/2403.10572 (2024) - [i82]Minqin Zhu, Anpeng Wu, Haoxuan Li, Ruoxuan Xiong, Bo Li, Xiaoqing Yang, Xuan Qin, Peng Zhen, Jiecheng Guo, Fei Wu, Kun Kuang:
Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation. CoRR abs/2403.14232 (2024) - [i81]Kunxi Li, Tianyu Zhan, Shengyu Zhang, Kun Kuang, Jiwei Li, Zhou Zhao, Fei Wu:
MergeNet: Knowledge Migration across Heterogeneous Models, Tasks, and Modalities. CoRR abs/2404.13322 (2024) - [i80]Ziheng Chen, Jia Wang, Jun Zhuang, Abbavaram Gowtham Reddy, Fabrizio Silvestri, Jin Huang, Kaushiki Nag, Kun Kuang, Xin Ning, Gabriele Tolomei:
Debiasing Machine Unlearning with Counterfactual Examples. CoRR abs/2404.15760 (2024) - [i79]Min Zhang, Haoxuan Li, Fei Wu, Kun Kuang:
MetaCoCo: A New Few-Shot Classification Benchmark with Spurious Correlation. CoRR abs/2404.19644 (2024) - [i78]Chengyuan Liu, Shihang Wang, Yangyang Kang, Lizhi Qing, Fubang Zhao, Changlong Sun, Kun Kuang, Fei Wu:
More Than Catastrophic Forgetting: Integrating General Capabilities For Domain-Specific LLMs. CoRR abs/2405.17830 (2024) - [i77]Shengyu Zhang, Ziqi Jiang, Jiangchao Yao, Fuli Feng, Kun Kuang, Zhou Zhao, Shuo Li, Hongxia Yang, Tat-Seng Chua, Fei Wu:
Causal Distillation for Alleviating Performance Heterogeneity in Recommender Systems. CoRR abs/2405.20626 (2024) - [i76]Ziyu Zhao, Leilei Gan, Guoyin Wang, Yuwei Hu, Tao Shen, Hongxia Yang, Kun Kuang, Fei Wu:
Retrieval-Augmented Mixture of LoRA Experts for Uploadable Machine Learning. CoRR abs/2406.16989 (2024) - [i75]Yuling Zhang, Anpeng Wu, Kun Kuang, Liang Du, Zixun Sun, Zhi Wang:
Stable Heterogeneous Treatment Effect Estimation across Out-of-Distribution Populations. CoRR abs/2407.03082 (2024) - [i74]Yingrong Wang, Haoxuan Li, Minqin Zhu, Anpeng Wu, Ruoxuan Xiong, Fei Wu, Kun Kuang:
Causal Inference with Complex Treatments: A Survey. CoRR abs/2407.14022 (2024) - [i73]Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Xiangwei Chen, Zexu Sun, Fei Wu, Kun Zhang:
Generalized Encouragement-Based Instrumental Variables for Counterfactual Regression. CoRR abs/2408.05428 (2024) - [i72]Kairong Han, Kun Kuang, Ziyu Zhao, Junjian Ye, Fei Wu:
Causal Agent based on Large Language Model. CoRR abs/2408.06849 (2024) - [i71]Jinluan Yang, Zhengyu Chen, Teng Xiao, Wenqiao Zhang, Yong Lin, Kun Kuang:
Leveraging Invariant Principle for Heterophilic Graph Structure Distribution Shifts. CoRR abs/2408.09490 (2024) - [i70]Yiquan Wu, Bo Tang, Chenyang Xi, Yu Yu, Pengyu Wang, Yifei Liu, Kun Kuang, Haiying Deng, Zhiyu Li, Feiyu Xiong, Jie Hu, Peng Cheng, Zhonghao Wang, Yi Wang, Yi Luo, Mingchuan Yang:
Xinyu: An Efficient LLM-based System for Commentary Generation. CoRR abs/2408.11609 (2024) - [i69]Tao Wu, Mengze Li, Jingyuan Chen, Wei Ji, Wang Lin, Jinyang Gao, Kun Kuang, Zhou Zhao, Fei Wu:
Semantic Alignment for Multimodal Large Language Models. CoRR abs/2408.12867 (2024) - [i68]Yuqi Bai, Ziyu Zhao, Minqin Zhu, Kun Kuang:
IntOPE: Off-Policy Evaluation in the Presence of Interference. CoRR abs/2408.13484 (2024) - [i67]Chengyuan Liu, Shihang Wang, Fubang Zhao, Kun Kuang, Yangyang Kang, Weiming Lu, Changlong Sun, Fei Wu:
RexUniNLU: Recursive Method with Explicit Schema Instructor for Universal NLU. CoRR abs/2409.05275 (2024) - [i66]Ziyu Zhao, Tao Shen, Didi Zhu, Zexi Li, Jing Su, Xuwu Wang, Kun Kuang, Fei Wu:
Merging LoRAs like Playing LEGO: Pushing the Modularity of LoRA to Extremes Through Rank-Wise Clustering. CoRR abs/2409.16167 (2024) - [i65]Chengyuan Liu, Shihang Wang, Lizhi Qing, Kun Kuang, Yangyang Kang, Changlong Sun, Fei Wu:
Gold Panning in Vocabulary: An Adaptive Method for Vocabulary Expansion of Domain-Specific LLMs. CoRR abs/2410.01188 (2024) - [i64]Anpeng Wu, Kun Kuang, Minqin Zhu, Yingrong Wang, Yujia Zheng, Kairong Han, Baohong Li, Guangyi Chen, Fei Wu, Kun Zhang:
Causality for Large Language Models. CoRR abs/2410.15319 (2024) - [i63]Jiahui Li, Tai-Wei Chang, Fengda Zhang, Kun Kuang, Long Chen:
R3HF: Reward Redistribution for Enhancing Reinforcement Learning from Human Feedback. CoRR abs/2411.08302 (2024) - [i62]Chengyuan Liu, Shihang Wang, Lizhi Qing, Jun Lin, Ji Zhang, Fei Wu, Kun Kuang:
Learning to Solve Domain-Specific Calculation Problems with Knowledge-Intensive Programs Generator. CoRR abs/2412.09280 (2024) - [i61]Jiahui Li, Tai-Wei Chang, Kun Kuang, Ximing Li, Long Chen, Jun Zhou:
Learning Causal Transition Matrix for Instance-dependent Label Noise. CoRR abs/2412.13516 (2024) - [i60]Zhonghua Jiang, Jimin Xu, Shengyu Zhang, Tao Shen, Jiwei Li, Kun Kuang, Haibin Cai, Fei Wu:
FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning. CoRR abs/2412.18904 (2024) - 2023
- [j20]Ziyu Zhao, Kun Kuang, Bo Li, Peng Cui, Runze Wu, Jun Xiao, Fei Wu:
Differentiated matching for individual and average treatment effect estimation. Data Min. Knowl. Discov. 37(1): 205-227 (2023) - [j19]Junkun Yuan, Xu Ma, Defang Chen, Kun Kuang, Fei Wu, Lanfen Lin:
Domain-Specific Bias Filtering for Single Labeled Domain Generalization. Int. J. Comput. Vis. 131(2): 552-571 (2023) - [j18]Fengda Zhang, Kun Kuang, Long Chen, Zhaoyang You, Tao Shen, Jun Xiao, Yin Zhang, Chao Wu, Fei Wu, Yueting Zhuang, Xiaolin Li:
Federated unsupervised representation learning. Frontiers Inf. Technol. Electron. Eng. 24(8): 1181-1193 (2023) - [j17]Tao Shen, Jie Zhang, Xinkang Jia, Fengda Zhang, Zheqi Lv, Kun Kuang, Chao Wu, Fei Wu:
Federated mutual learning: a collaborative machine learning method for heterogeneous data, models, and objectives. Frontiers Inf. Technol. Electron. Eng. 24(10): 1390-1402 (2023) - [j16]Shengyu Zhang, Fuli Feng, Kun Kuang, Wenqiao Zhang, Zhou Zhao, Hongxia Yang, Tat-Seng Chua, Fei Wu:
Personalized Latent Structure Learning for Recommendation. IEEE Trans. Pattern Anal. Mach. Intell. 45(8): 10285-10299 (2023) - [j15]Junkun Yuan, Xu Ma, Ruoxuan Xiong, Mingming Gong, Xiangyu Liu, Fei Wu, Lanfen Lin, Kun Kuang:
Instrumental Variable-Driven Domain Generalization with Unobserved Confounders. ACM Trans. Knowl. Discov. Data 17(8): 118:1-118:21 (2023) - [j14]Anpeng Wu, Junkun Yuan, Kun Kuang, Bo Li, Runze Wu, Qiang Zhu, Yueting Zhuang, Fei Wu:
Learning Decomposed Representations for Treatment Effect Estimation. IEEE Trans. Knowl. Data Eng. 35(5): 4989-5001 (2023) - [j13]Kun Kuang, Haotian Wang, Yue Liu, Ruoxuan Xiong, Runze Wu, Weiming Lu, Yueting Zhuang, Fei Wu, Peng Cui, Bo Li:
Stable Prediction With Leveraging Seed Variable. IEEE Trans. Knowl. Data Eng. 35(6): 6392-6404 (2023) - [j12]Jiangchao Yao, Shengyu Zhang, Yang Yao, Feng Wang, Jianxin Ma, Jianwei Zhang, Yunfei Chu, Luo Ji, Kunyang Jia, Tao Shen, Anpeng Wu, Fengda Zhang, Ziqi Tan, Kun Kuang, Chao Wu, Fei Wu, Jingren Zhou, Hongxia Yang:
Edge-Cloud Polarization and Collaboration: A Comprehensive Survey for AI. IEEE Trans. Knowl. Data Eng. 35(7): 6866-6886 (2023) - [j11]Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li:
Distributionally Robust Learning With Stable Adversarial Training. IEEE Trans. Knowl. Data Eng. 35(11): 11288-11300 (2023) - [j10]Junkun Yuan, Xu Ma, Defang Chen, Fei Wu, Lanfen Lin, Kun Kuang:
Collaborative Semantic Aggregation and Calibration for Federated Domain Generalization. IEEE Trans. Knowl. Data Eng. 35(12): 12528-12541 (2023) - [c80]Yinjie Jiang, Ying Wei, Fei Wu, Zhengxing Huang, Kun Kuang, Zhihua Wang:
Learning Chemical Rules of Retrosynthesis with Pre-training. AAAI 2023: 5113-5121 - [c79]Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Minqing Zhu, Yuxuan Liu, Bo Li, Furui Liu, Zhihua Wang, Fei Wu:
Learning Instrumental Variable from Data Fusion for Treatment Effect Estimation. AAAI 2023: 10324-10332 - [c78]Qi Tian, Kun Kuang, Furui Liu, Baoxiang Wang:
Learning from Good Trajectories in Offline Multi-Agent Reinforcement Learning. AAAI 2023: 11672-11680 - [c77]Yiquan Wu, Weiming Lu, Yating Zhang, Adam Jatowt, Jun Feng, Changlong Sun, Fei Wu, Kun Kuang:
Focus-aware Response Generation in Inquiry Conversation. ACL (Findings) 2023: 12585-12599 - [c76]Kun Kuang:
Causal Inspired Trustworthy Machine Learning. ACM TUR-C 2023: 3-4 - [c75]Shanqi Liu, Yujing Hu, Runze Wu, Dong Xing, Yu Xiong, Changjie Fan, Kun Kuang, Yong Liu:
Adaptive Value Decomposition with Greedy Marginal Contribution Computation for Cooperative Multi-Agent Reinforcement Learning. AAMAS 2023: 31-39 - [c74]Yuxuan Liu, Kun Kuang, Fengda Zhang, Fei Wu:
FairDR: Ensuring Fairness in Mixed Data of Fairly and Unfairly Treated Instances. CICAI (2) 2023: 3-14 - [c73]Kairui Fu, Qiaowei Miao, Shengyu Zhang, Kun Kuang, Fei Wu:
End-to-End Optimization of Quantization-Based Structure Learning and Interventional Next-Item Recommendation. CICAI (1) 2023: 415-429 - [c72]Zheqi Lv, Feng Wang, Shengyu Zhang, Wenqiao Zhang, Kun Kuang, Fei Wu:
Parameters Efficient Fine-Tuning for Long-Tailed Sequential Recommendation. CICAI (1) 2023: 442-459 - [c71]Yiquan Wu, Siying Zhou, Yifei Liu, Weiming Lu, Xiaozhong Liu, Yating Zhang, Changlong Sun, Fei Wu, Kun Kuang:
Precedent-Enhanced Legal Judgment Prediction with LLM and Domain-Model Collaboration. EMNLP 2023: 12060-12075 - [c70]Leilei Gan, Baokui Li, Kun Kuang, Yating Zhang, Lei Wang, Anh Tuan Luu, Yi Yang, Fei Wu:
Exploiting Contrastive Learning and Numerical Evidence for Confusing Legal Judgment Prediction. EMNLP (Findings) 2023: 12174-12185 - [c69]Chengyuan Liu, Fubang Zhao, Yangyang Kang, Jingyuan Zhang, Xiang Zhou, Changlong Sun, Kun Kuang, Fei Wu:
RexUIE: A Recursive Method with Explicit Schema Instructor for Universal Information Extraction. EMNLP (Findings) 2023: 15342-15359 - [c68]Didi Zhu, Yinchuan Li, Junkun Yuan, Zexi Li, Kun Kuang, Chao Wu:
Universal Domain Adaptation via Compressive Attention Matching. ICCV 2023: 6951-6962 - [c67]Min Zhang, Junkun Yuan, Yue He, Wenbin Li, Zhengyu Chen, Kun Kuang:
MAP: Towards Balanced Generalization of IID and OOD through Model-Agnostic Adapters. ICCV 2023: 11887-11897 - [c66]Fengda Zhang, Kun Kuang, Long Chen, Yuxuan Liu, Chao Wu, Jun Xiao:
Fairness-aware Contrastive Learning with Partially Annotated Sensitive Attributes. ICLR 2023 - [c65]Chenxi Liu, Kun Kuang:
Causal Structure Learning for Latent Intervened Non-stationary Data. ICML 2023: 21756-21777 - [c64]Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Bo Li, Fei Wu:
Stable Estimation of Heterogeneous Treatment Effects. ICML 2023: 37496-37510 - [c63]Haoxuan Li, Chunyuan Zheng, Peng Wu, Kun Kuang, Yue Liu, Peng Cui:
Who Should Be Given Incentives? Counterfactual Optimal Treatment Regimes Learning for Recommendation. KDD 2023: 1235-1247 - [c62]Yunze Tong, Junkun Yuan, Min Zhang, Didi Zhu, Keli Zhang, Fei Wu, Kun Kuang:
Quantitatively Measuring and Contrastively Exploring Heterogeneity for Domain Generalization. KDD 2023: 2189-2200 - [c61]Haotian Wang, Kun Kuang, Haoang Chi, Longqi Yang, Mingyang Geng, Wanrong Huang, Wenjing Yang:
Treatment Effect Estimation with Adjustment Feature Selection. KDD 2023: 2290-2301 - [c60]Thuc Duy Le, Jiuyong Li, Robert Ness, Sofia Triantafillou, Shohei Shimizu, Peng Cui, Kun Kuang, Jian Pei, Fei Wang, Mattia Prosperi:
Preface: The 2023 ACM SIGKDD Workshop on Causal Discovery, Prediction and Decision. CDPD 2023: 1-2 - [c59]Shengyu Zhang, Yunze Tong, Kun Kuang, Fuli Feng, Jiezhong Qiu, Jin Yu, Zhou Zhao, Hongxia Yang, Zhongfei Zhang, Fei Wu:
Stable Prediction on Graphs with Agnostic Distribution Shifts. CDPD 2023: 49-74 - [c58]Tianqi Zhao, Ming Kong, Tian Liang, Qiang Zhu, Kun Kuang, Fei Wu:
CLAP: Contrastive Language-Audio Pre-training Model for Multi-modal Sentiment Analysis. ICMR 2023: 622-626 - [c57]Didi Zhu, Yinchuan Li, Yunfeng Shao, Jianye Hao, Fei Wu, Kun Kuang, Jun Xiao, Chao Wu:
Generalized Universal Domain Adaptation with Generative Flow Networks. ACM Multimedia 2023: 8304-8315 - [c56]Jiahui Li, Kun Kuang, Baoxiang Wang, Xingchen Li, Fei Wu, Jun Xiao, Long Chen:
Two Heads are Better Than One: A Simple Exploration Framework for Efficient Multi-Agent Reinforcement Learning. NeurIPS 2023 - [c55]Junkun Yuan, Xinyu Zhang, Hao Zhou, Jian Wang, Zhongwei Qiu, Zhiyin Shao, Shaofeng Zhang, Sifan Long, Kun Kuang, Kun Yao, Junyu Han, Errui Ding, Lanfen Lin, Fei Wu, Jingdong Wang:
HAP: Structure-Aware Masked Image Modeling for Human-Centric Perception. NeurIPS 2023 - [c54]Yifei Liu, Yiquan Wu, Yating Zhang, Changlong Sun, Weiming Lu, Fei Wu, Kun Kuang:
ML-LJP: Multi-Law Aware Legal Judgment Prediction. SIGIR 2023: 1023-1034 - [c53]Dingyuan Zhu, Daixin Wang, Zhiqiang Zhang, Kun Kuang, Yan Zhang, Yulin Kang, Jun Zhou:
Graph Neural Network with Two Uplift Estimators for Label-Scarcity Individual Uplift Modeling. WWW 2023: 395-405 - [c52]Zheqi Lv, Wenqiao Zhang, Shengyu Zhang, Kun Kuang, Feng Wang, Yongwei Wang, Zhengyu Chen, Tao Shen, Hongxia Yang, Beng Chin Ooi, Fei Wu:
DUET: A Tuning-Free Device-Cloud Collaborative Parameters Generation Framework for Efficient Device Model Generalization. WWW 2023: 3077-3085 - [e1]Thuc Duy Le, Jiuyong Li, Robert Ness, Sofia Triantafillou, Shohei Shimizu, Peng Cui, Kun Kuang, Jian Pei, Fei Wang, Mattia Prosperi:
The KDD'23 Workshop on Causal Discovery, Prediction and Decision, 07 August 2023, Long Beach, CA, USA. Proceedings of Machine Learning Research 218, PMLR 2023 [contents] - [i59]Shanqi Liu, Yujing Hu, Runze Wu, Dong Xing, Yu Xiong, Changjie Fan, Kun Kuang, Yong Liu:
Adaptive Value Decomposition with Greedy Marginal Contribution Computation for Cooperative Multi-Agent Reinforcement Learning. CoRR abs/2302.06872 (2023) - [i58]Zheqi Lv, Zhengyu Chen, Shengyu Zhang, Kun Kuang, Wenqiao Zhang, Mengze Li, Beng Chin Ooi, Fei Wu:
IDEAL: Toward High-efficiency Device-Cloud Collaborative and Dynamic Recommendation System. CoRR abs/2302.07335 (2023) - [i57]Didi Zhu, Yinchuan Li, Junkun Yuan, Zexi Li, Yunfeng Shao, Kun Kuang, Chao Wu:
Universal Domain Adaptation via Compressive Attention Matching. CoRR abs/2304.11862 (2023) - [i56]Chengyuan Liu, Fubang Zhao, Yangyang Kang, Jingyuan Zhang, Xiang Zhou, Changlong Sun, Fei Wu, Kun Kuang:
RexUIE: A Recursive Method with Explicit Schema Instructor for Universal Information Extraction. CoRR abs/2304.14770 (2023) - [i55]Didi Zhu, Yinchuan Li, Yunfeng Shao, Jianye Hao, Fei Wu, Kun Kuang, Jun Xiao, Chao Wu:
Generalized Universal Domain Adaptation with Generative Flow Networks. CoRR abs/2305.04466 (2023) - [i54]Yunze Tong, Junkun Yuan, Min Zhang, Didi Zhu, Keli Zhang, Fei Wu, Kun Kuang:
Quantitatively Measuring and Contrastively Exploring Heterogeneity for Domain Generalization. CoRR abs/2305.15889 (2023) - [i53]Didi Zhu, Yinchuan Li, Min Zhang, Junkun Yuan, Jiashuo Liu, Zexi Li, Kun Kuang, Chao Wu:
Bridging the Gap: Neural Collapse Inspired Prompt Tuning for Generalization under Class Imbalance. CoRR abs/2306.15955 (2023) - [i52]Anpeng Wu, Haoxuan Li, Kun Kuang, Keli Zhang, Fei Wu:
Hierarchical Topological Ordering with Conditional Independence Test for Limited Time Series. CoRR abs/2308.08148 (2023) - [i51]Junao Shen, Long Chen, Kun Kuang, Fei Wu, Tian Feng, Wei Zhang:
MEDOE: A Multi-Expert Decoder and Output Ensemble Framework for Long-tailed Semantic Segmentation. CoRR abs/2308.08213 (2023) - [i50]Chengyuan Liu, Fubang Zhao, Lizhi Qing, Yangyang Kang, Changlong Sun, Kun Kuang, Fei Wu:
A Chinese Prompt Attack Dataset for LLMs with Evil Content. CoRR abs/2309.11830 (2023) - [i49]Yiquan Wu, Siying Zhou, Yifei Liu, Weiming Lu, Xiaozhong Liu, Yating Zhang, Changlong Sun, Fei Wu, Kun Kuang:
Precedent-Enhanced Legal Judgment Prediction with LLM and Domain-Model Collaboration. CoRR abs/2310.09241 (2023) - [i48]Junkun Yuan, Xinyu Zhang, Hao Zhou, Jian Wang, Zhongwei Qiu, Zhiyin Shao, Shaofeng Zhang, Sifan Long, Kun Kuang, Kun Yao, Junyu Han, Errui Ding, Lanfen Lin, Fei Wu, Jingdong Wang:
HAP: Structure-Aware Masked Image Modeling for Human-Centric Perception. CoRR abs/2310.20695 (2023) - [i47]Zhengyu Chen, Teng Xiao, Kun Kuang, Zheqi Lv, Min Zhang, Jinluan Yang, Chengqiang Lu, Hongxia Yang, Fei Wu:
Learning to Reweight for Graph Neural Network. CoRR abs/2312.12475 (2023) - 2022
- [j9]Ming Kong, Qing Guo, Shuowen Zhou, Mengze Li, Kun Kuang, Zhengxing Huang, Fei Wu, Xiaohong Chen, Qiang Zhu:
Attribute-aware interpretation learning for thyroid ultrasound diagnosis. Artif. Intell. Medicine 131: 102344 (2022) - [j8]Bin Wei, Kun Kuang, Changlong Sun, Jun Feng, Yating Zhang, Xinli Zhu, Jianghong Zhou, Yinsheng Zhai, Fei Wu:
A full-process intelligent trial system for smart court. Frontiers Inf. Technol. Electron. Eng. 23(2): 186-206 (2022) - [j7]Kun Kuang, Hengtao Zhang, Runze Wu, Fei Wu, Yueting Zhuang, Aijun Zhang:
Balance-Subsampled Stable Prediction Across Unknown Test Data. ACM Trans. Knowl. Discov. Data 16(3): 45:1-45:21 (2022) - [j6]Junkun Yuan, Anpeng Wu, Kun Kuang, Bo Li, Runze Wu, Fei Wu, Lanfen Lin:
Auto IV: Counterfactual Prediction via Automatic Instrumental Variable Decomposition. ACM Trans. Knowl. Discov. Data 16(4): 74:1-74:20 (2022) - [j5]Kun Kuang, Peng Cui, Hao Zou, Bo Li, Jianrong Tao, Fei Wu, Shiqiang Yang:
Data-Driven Variable Decomposition for Treatment Effect Estimation. IEEE Trans. Knowl. Data Eng. 34(5): 2120-2134 (2022) - [c51]Leilei Gan, Yuxian Meng, Kun Kuang, Xiaofei Sun, Chun Fan, Fei Wu, Jiwei Li:
Dependency Parsing as MRC-based Span-Span Prediction. ACL (1) 2022: 2427-2437 - [c50]Yemin Yu, Kun Kuang, Jiangchao Yang, Zeke Wang, Kunyang Jia, Weiming Lu, Hongxia Yang, Fei Wu:
Multi-objective Meta-return Reinforcement Learning for Sequential Recommendation. CICAI (2) 2022: 95-111 - [c49]Siying Zhou, Yifei Liu, Yiquan Wu, Kun Kuang, Chunyan Zheng, Fei Wu:
Similar Case Based Prison Term Prediction. CICAI (3) 2022: 284-297 - [c48]Tianqi Zhao, Ming Kong, Kun Kuang, Zhengxing Huang, Qiang Zhu, Fei Wu:
Connecting Patients with Pre-diagnosis: A Multiple Graph Regularized Method for Mental Disorder Diagnosis. CICAI (2) 2022: 362-374 - [c47]Yiquan Wu, Yifei Liu, Weiming Lu, Yating Zhang, Jun Feng, Changlong Sun, Fei Wu, Kun Kuang:
Towards Interactivity and Interpretability: A Rationale-based Legal Judgment Prediction Framework. EMNLP 2022: 4787-4799 - [c46]Chengyuan Liu, Leilei Gan, Kun Kuang, Fei Wu:
Investigating the Robustness of Natural Language Generation from Logical Forms via Counterfactual Samples. EMNLP 2022: 5499-5512 - [c45]Zhengyu Chen, Teng Xiao, Kun Kuang:
BA-GNN: On Learning Bias-Aware Graph Neural Network. ICDE 2022: 3012-3024 - [c44]Yuxuan Si, Zhengqing Fang, Kun Kuang, Zhengxing Huang, Yu-Feng Yao, Fei Wu:
Disentangled Sequential Autoencoder with Local Consistency for Infectious Keratitis Diagnosis. ICIP 2022: 3893-3897 - [c43]Yinjie Jiang, Zhengyu Chen, Kun Kuang, Luotian Yuan, Xinhai Ye, Zhihua Wang, Fei Wu, Ying Wei:
The Role of Deconfounding in Meta-learning. ICML 2022: 10161-10176 - [c42]Jiahui Li, Kun Kuang, Baoxiang Wang, Furui Liu, Long Chen, Changjie Fan, Fei Wu, Jun Xiao:
Deconfounded Value Decomposition for Multi-Agent Reinforcement Learning. ICML 2022: 12843-12856 - [c41]Anpeng Wu, Kun Kuang, Bo Li, Fei Wu:
Instrumental Variable Regression with Confounder Balancing. ICML 2022: 24056-24075 - [c40]Shuang Luo, Yinchuan Li, Jiahui Li, Kun Kuang, Furui Liu, Yunfeng Shao, Chao Wu:
S2RL: Do We Really Need to Perceive All States in Deep Multi-Agent Reinforcement Learning? KDD 2022: 1183-1191 - [c39]Haotian Wang, Wenjing Yang, Longqi Yang, Anpeng Wu, Liyang Xu, Jing Ren, Fei Wu, Kun Kuang:
Estimating Individualized Causal Effect with Confounded Instruments. KDD 2022: 1857-1867 - [c38]Jiannan Guo, Yangyang Kang, Yu Duan, Xiaozhong Liu, Siliang Tang, Wenqiao Zhang, Kun Kuang, Changlong Sun, Fei Wu:
Collaborative Intelligence Orchestration: Inconsistency-Based Fusion of Semi-Supervised Learning and Active Learning. KDD 2022: 2935-2945 - [c37]Ming Kong, Zhengxing Huang, Kun Kuang, Qiang Zhu, Fei Wu:
TranSQ: Transformer-Based Semantic Query for Medical Report Generation. MICCAI (8) 2022: 610-620 - [c36]Junkun Yuan, Xu Ma, Defang Chen, Kun Kuang, Fei Wu, Lanfen Lin:
Label-Efficient Domain Generalization via Collaborative Exploration and Generalization. ACM Multimedia 2022: 2361-2370 - [c35]Qi Tian, Kun Kuang, Kelu Jiang, Furui Liu, Zhihua Wang, Fei Wu:
ConfounderGAN: Protecting Image Data Privacy with Causal Confounder. NeurIPS 2022 - [c34]Yemin Yu, Ying Wei, Kun Kuang, Zhengxing Huang, Huaxiu Yao, Fei Wu:
GRASP: Navigating Retrosynthetic Planning with Goal-driven Policy. NeurIPS 2022 - [c33]Ziqi Tan, Shengyu Zhang, Nuanxin Hong, Kun Kuang, Yifan Yu, Jin Yu, Zhou Zhao, Hongxia Yang, Shiyuan Pan, Jingren Zhou, Fei Wu:
Uncovering Causal Effects of Online Short Videos on Consumer Behaviors. WSDM 2022: 997-1006 - [i46]Shaohua Fan, Xiao Wang, Chuan Shi, Kun Kuang, Nian Liu, Bai Wang:
Debiased Graph Neural Networks with Agnostic Label Selection Bias. CoRR abs/2201.07708 (2022) - [i45]Jiannan Guo, Yangyang Kang, Yu Duan, Xiaozhong Liu, Siliang Tang, Wenqiao Zhang, Kun Kuang, Changlong Sun, Fei Wu:
Collaborative Intelligence Orchestration: Inconsistency-Based Fusion of Semi-Supervised Learning and Active Learning. CoRR abs/2206.03288 (2022) - [i44]Shuang Luo, Yinchuan Li, Jiahui Li, Kun Kuang, Furui Liu, Yunfeng Shao, Chao Wu:
S2RL: Do We Really Need to Perceive All States in Deep Multi-Agent Reinforcement Learning? CoRR abs/2206.11054 (2022) - [i43]Junkun Yuan, Xu Ma, Defang Chen, Kun Kuang, Fei Wu, Lanfen Lin:
Label-Efficient Domain Generalization via Collaborative Exploration and Generalization. CoRR abs/2208.03644 (2022) - [i42]Zheqi Lv, Feng Wang, Shengyu Zhang, Kun Kuang, Hongxia Yang, Fei Wu:
Personalizing Intervened Network for Long-tailed Sequential User Behavior Modeling. CoRR abs/2208.09130 (2022) - [i41]Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Minqing Zhu, Yuxuan Liu, Bo Li, Furui Liu, Zhihua Wang, Fei Wu:
Treatment Effect Estimation with Unmeasured Confounders in Data Fusion. CoRR abs/2208.10912 (2022) - [i40]Zheqi Lv, Feng Wang, Kun Kuang, Yongwei Wang, Zhengyu Chen, Tao Shen, Hongxia Yang, Fei Wu:
MetaNetwork: A Task-agnostic Network Parameters Generation Framework for Improving Device Model Generalization. CoRR abs/2209.05227 (2022) - [i39]Qiaowei Miao, Junkun Yuan, Kun Kuang:
Domain Generalization via Contrastive Causal Learning. CoRR abs/2210.02655 (2022) - [i38]Chengyuan Liu, Leilei Gan, Kun Kuang, Fei Wu:
Investigating the Robustness of Natural Language Generation from Logical Forms via Counterfactual Samples. CoRR abs/2210.08548 (2022) - [i37]Ziyu Zhao, Kun Kuang, Ruoxuan Xiong, Fei Wu:
Learning Individual Treatment Effects under Heterogeneous Interference in Networks. CoRR abs/2210.14080 (2022) - [i36]Leilei Gan, Baokui Li, Kun Kuang, Yi Yang, Fei Wu:
Exploiting Contrastive Learning and Numerical Evidence for Improving Confusing Legal Judgment Prediction. CoRR abs/2211.08238 (2022) - [i35]Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Bo Li, Fei Wu:
Confounder Balancing for Instrumental Variable Regression with Latent Variable. CoRR abs/2211.10008 (2022) - [i34]Qi Tian, Kun Kuang, Furui Liu, Baoxiang Wang:
Learning From Good Trajectories in Offline Multi-Agent Reinforcement Learning. CoRR abs/2211.15612 (2022) - [i33]Qi Tian, Kun Kuang, Kelu Jiang, Furui Liu, Zhihua Wang, Fei Wu:
ConfounderGAN: Protecting Image Data Privacy with Causal Confounder. CoRR abs/2212.01767 (2022) - [i32]Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Fei Wu:
Instrumental Variables in Causal Inference and Machine Learning: A Survey. CoRR abs/2212.05778 (2022) - 2021
- [j4]Kun Kuang, Yunzhe Li, Bo Li, Peng Cui, Hongxia Yang, Jianrong Tao, Fei Wu:
Continuous treatment effect estimation via generative adversarial de-confounding. Data Min. Knowl. Discov. 35(6): 2467-2497 (2021) - [c32]Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li, Yishi Lin:
Stable Adversarial Learning under Distributional Shifts. AAAI 2021: 8662-8670 - [c31]Leilei Gan, Kun Kuang, Yi Yang, Fei Wu:
Judgment Prediction via Injecting Legal Knowledge into Neural Networks. AAAI 2021: 12866-12874 - [c30]Yuxiao Lin, Yuxian Meng, Xiaofei Sun, Qinghong Han, Kun Kuang, Jiwei Li, Fei Wu:
BertGCN: Transductive Text Classification by Combining GNN and BERT. ACL/IJCNLP (Findings) 2021: 1456-1462 - [c29]Ziyu Zhao, Kun Kuang, Fei Wu:
Estimating Treatment Effect via Differentiated Confounder Matching. CICAI 2021: 689-699 - [c28]Shengyu Zhang, Tan Jiang, Tan Wang, Kun Kuang, Zhou Zhao, Jianke Zhu, Jin Yu, Hongxia Yang, Fei Wu:
DeVLBert: Out-of-Distribution Visio-Linguistic Pretraining With Causality. CVPR Workshops 2021: 1744-1747 - [c27]Shengyu Zhang, Tan Jiang, Qinghao Huang, Ziqi Tan, Kun Kuang, Zhou Zhao, Siliang Tang, Jin Yu, Hongxia Yang, Yi Yang, Fei Wu:
Grounded, Controllable and Debiased Image Completion With Lexical Semantics. CVPR Workshops 2021: 1748-1751 - [c26]Jiannan Guo, Haochen Shi, Yangyang Kang, Kun Kuang, Siliang Tang, Zhuoren Jiang, Changlong Sun, Fei Wu, Yueting Zhuang:
Semi-supervised Active Learning for Semi-supervised Models: Exploit Adversarial Examples with Graph-based Virtual Labels. ICCV 2021: 2876-2885 - [c25]Xin Wang, Shuyi Fan, Kun Kuang, Wenwu Zhu:
Explainable Automated Graph Representation Learning with Hyperparameter Importance. ICML 2021: 10727-10737 - [c24]Jiahui Li, Kun Kuang, Baoxiang Wang, Furui Liu, Long Chen, Fei Wu, Jun Xiao:
Shapley Counterfactual Credits for Multi-Agent Reinforcement Learning. KDD 2021: 934-942 - [c23]Qi Tian, Kun Kuang, Kelu Jiang, Fei Wu, Yisen Wang:
Analysis and Applications of Class-wise Robustness in Adversarial Training. KDD 2021: 1561-1570 - [c22]Jiahui Li, Kun Kuang, Lin Li, Long Chen, Songyang Zhang, Jian Shao, Jun Xiao:
Instance-wise or Class-wise? A Tale of Neighbor Shapley for Concept-based Explanation. ACM Multimedia 2021: 3664-3672 - [c21]Shengyu Zhang, Donghui Wang, Zhou Zhao, Siliang Tang, Kun Kuang, Di Xie, Fei Wu:
MGD-GAN: Text-to-Pedestrian Generation Through Multi-grained Discrimination. PRCV (2) 2021: 662-673 - [i31]Yuxiao Lin, Yuxian Meng, Xiaofei Sun, Qinghong Han, Kun Kuang, Jiwei Li, Fei Wu:
BertGCN: Transductive Text Classification by Combining GCN and BERT. CoRR abs/2105.05727 (2021) - [i30]Leilei Gan, Yuxian Meng, Kun Kuang, Xiaofei Sun, Chun Fan, Fei Wu, Jiwei Li:
Dependency Parsing as MRC-based Span-Span Prediction. CoRR abs/2105.07654 (2021) - [i29]Qi Tian, Kun Kuang, Kelu Jiang, Fei Wu, Yisen Wang:
Analysis and Applications of Class-wise Robustness in Adversarial Training. CoRR abs/2105.14240 (2021) - [i28]Jiahui Li, Kun Kuang, Baoxiang Wang, Furui Liu, Long Chen, Fei Wu, Jun Xiao:
Shapley Counterfactual Credits for Multi-Agent Reinforcement Learning. CoRR abs/2106.00285 (2021) - [i27]Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li:
Distributionally Robust Learning with Stable Adversarial Training. CoRR abs/2106.15791 (2021) - [i26]Junkun Yuan, Anpeng Wu, Kun Kuang, Bo Li, Runze Wu, Fei Wu, Lanfen Lin:
Auto IV: Counterfactual Prediction via Automatic Instrumental Variable Decomposition. CoRR abs/2107.05884 (2021) - [i25]Jiahui Li, Kun Kuang, Lin Li, Long Chen, Songyang Zhang, Jian Shao, Jun Xiao:
Instance-wise or Class-wise? A Tale of Neighbor Shapley for Concept-based Explanation. CoRR abs/2109.01369 (2021) - [i24]Junkun Yuan, Xu Ma, Defang Chen, Kun Kuang, Fei Wu, Lanfen Lin:
Domain-Specific Bias Filtering for Single Labeled Domain Generalization. CoRR abs/2110.00726 (2021) - [i23]Junkun Yuan, Xu Ma, Kun Kuang, Ruoxuan Xiong, Mingming Gong, Lanfen Lin:
Learning Domain-Invariant Relationship with Instrumental Variable for Domain Generalization. CoRR abs/2110.01438 (2021) - [i22]Shengyu Zhang, Kun Kuang, Jiezhong Qiu, Jin Yu, Zhou Zhao, Hongxia Yang, Zhongfei Zhang, Fei Wu:
Stable Prediction on Graphs with Agnostic Distribution Shift. CoRR abs/2110.03865 (2021) - [i21]Junkun Yuan, Xu Ma, Defang Chen, Kun Kuang, Fei Wu, Lanfen Lin:
Do We Need to Directly Access the Source Datasets for Domain Generalization? CoRR abs/2110.06736 (2021) - [i20]Leilei Gan, Yating Zhang, Kun Kuang, Lin Yuan, Shuo Li, Changlong Sun, Xiaozhong Liu, Fei Wu:
Dialogue Inspectional Summarization with Factual Inconsistency Awareness. CoRR abs/2111.03284 (2021) - [i19]Fengda Zhang, Kun Kuang, Yuxuan Liu, Chao Wu, Fei Wu, Jiaxun Lu, Yunfeng Shao, Jun Xiao:
Unified Group Fairness on Federated Learning. CoRR abs/2111.04986 (2021) - [i18]Jiangchao Yao, Shengyu Zhang, Yang Yao, Feng Wang, Jianxin Ma, Jianwei Zhang, Yunfei Chu, Luo Ji, Kunyang Jia, Tao Shen, Anpeng Wu, Fengda Zhang, Ziqi Tan, Kun Kuang, Chao Wu, Fei Wu, Jingren Zhou, Hongxia Yang:
Edge-Cloud Polarization and Collaboration: A Comprehensive Survey. CoRR abs/2111.06061 (2021) - [i17]Qi Tian, Kun Kuang, Baoxiang Wang, Furui Liu, Fei Wu:
Multi-agent Communication with Graph Information Bottleneck under Limited Bandwidth. CoRR abs/2112.10374 (2021) - 2020
- [j3]Fashen Li, Lian Li, Jianping Yin, Liang Huang, Qingguo Zhou, Ning An, Yong Zhang, Li Liu, Jialin Zhang, Kun Kuang, Lei Yang, Zhixi Wu, Lianchun Yu:
Machine knowledge and human cognition. Big Data Min. Anal. 3(4): 292-299 (2020) - [j2]Kun Kuang, Peng Cui, Bo Li, Meng Jiang, Yashen Wang, Fei Wu, Shiqiang Yang:
Treatment Effect Estimation via Differentiated Confounder Balancing and Regression. ACM Trans. Knowl. Discov. Data 14(1): 6:1-6:25 (2020) - [c20]Kun Kuang, Ruoxuan Xiong, Peng Cui, Susan Athey, Bo Li:
Stable Prediction with Model Misspecification and Agnostic Distribution Shift. AAAI 2020: 4485-4492 - [c19]Zheyan Shen, Peng Cui, Tong Zhang, Kun Kuang:
Stable Learning via Sample Reweighting. AAAI 2020: 5692-5699 - [c18]Mengze Li, Kun Kuang, Qiang Zhu, Xiaohong Chen, Qing Guo, Fei Wu:
IB-M: A Flexible Framework to Align an Interpretable Model and a Black-box Model. BIBM 2020: 643-649 - [c17]Yufei Feng, Fuyu Lv, Binbin Hu, Fei Sun, Kun Kuang, Yang Liu, Qingwen Liu, Wenwu Ou:
MTBRN: Multiplex Target-Behavior Relation Enhanced Network for Click-Through Rate Prediction. CIKM 2020: 2421-2428 - [c16]Yiquan Wu, Kun Kuang, Yating Zhang, Xiaozhong Liu, Changlong Sun, Jun Xiao, Yueting Zhuang, Luo Si, Fei Wu:
De-Biased Court's View Generation with Causality. EMNLP (1) 2020: 763-780 - [c15]Xiao Wang, Shaohua Fan, Kun Kuang, Chuan Shi, Jiawei Liu, Bai Wang:
Decorrelated Clustering with Data Selection Bias. IJCAI 2020: 2177-2183 - [c14]Yunzhe Li, Kun Kuang, Bo Li, Peng Cui, Jianrong Tao, Hongxia Yang, Fei Wu:
Continuous Treatment Effect Estimation via Generative Adversarial De-confounding. CD@KDD 2020: 4-22 - [c13]Renzhe Xu, Peng Cui, Kun Kuang, Bo Li, Linjun Zhou, Zheyan Shen, Wei Cui:
Algorithmic Decision Making with Conditional Fairness. KDD 2020: 2125-2135 - [c12]Shengyu Zhang, Ziqi Tan, Zhou Zhao, Jin Yu, Kun Kuang, Tan Jiang, Jingren Zhou, Hongxia Yang, Fei Wu:
Comprehensive Information Integration Modeling Framework for Video Titling. KDD 2020: 2744-2754 - [c11]Zhengqing Fang, Kun Kuang, Yuxiao Lin, Fei Wu, Yu-Feng Yao:
Concept-based Explanation for Fine-grained Images and Its Application in Infectious Keratitis Classification. ACM Multimedia 2020: 700-708 - [c10]Shengyu Zhang, Ziqi Tan, Jin Yu, Zhou Zhao, Kun Kuang, Jie Liu, Jingren Zhou, Hongxia Yang, Fei Wu:
Poet: Product-oriented Video Captioner for E-commerce. ACM Multimedia 2020: 1292-1301 - [c9]Shengyu Zhang, Tan Jiang, Tan Wang, Kun Kuang, Zhou Zhao, Jianke Zhu, Jin Yu, Hongxia Yang, Fei Wu:
DeVLBert: Learning Deconfounded Visio-Linguistic Representations. ACM Multimedia 2020: 4373-4382 - [i16]Kun Kuang, Ruoxuan Xiong, Peng Cui, Susan Athey, Bo Li:
Stable Prediction with Model Misspecification and Agnostic Distribution Shift. CoRR abs/2001.11713 (2020) - [i15]Kun Kuang, Hengtao Zhang, Fei Wu, Yueting Zhuang, Aijun Zhang:
Balance-Subsampled Stable Prediction. CoRR abs/2006.04381 (2020) - [i14]Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li, Yishi Lin:
Invariant Adversarial Learning for Distributional Robustness. CoRR abs/2006.04414 (2020) - [i13]Kun Kuang, Bo Li, Peng Cui, Yue Liu, Jianrong Tao, Yueting Zhuang, Fei Wu:
Stable Prediction via Leveraging Seed Variable. CoRR abs/2006.05076 (2020) - [i12]Anpeng Wu, Kun Kuang, Junkun Yuan, Bo Li, Pan Zhou, Jianrong Tao, Qiang Zhu, Yueting Zhuang, Fei Wu:
Learning Decomposed Representation for Counterfactual Inference. CoRR abs/2006.07040 (2020) - [i11]Renzhe Xu, Peng Cui, Kun Kuang, Bo Li, Linjun Zhou, Zheyan Shen, Wei Cui:
Algorithmic Decision Making with Conditional Fairness. CoRR abs/2006.10483 (2020) - [i10]Shengyu Zhang, Ziqi Tan, Jin Yu, Zhou Zhao, Kun Kuang, Tan Jiang, Jingren Zhou, Hongxia Yang, Fei Wu:
Comprehensive Information Integration Modeling Framework for Video Titling. CoRR abs/2006.13608 (2020) - [i9]Xiao Wang, Shaohua Fan, Kun Kuang, Chuan Shi, Jiawei Liu, Bai Wang:
Decorrelated Clustering with Data Selection Bias. CoRR abs/2006.15874 (2020) - [i8]Yufei Feng, Fuyu Lv, Binbin Hu, Fei Sun, Kun Kuang, Yang Liu, Qingwen Liu, Wenwu Ou:
MTBRN: Multiplex Target-Behavior Relation Enhanced Network for Click-Through Rate Prediction. CoRR abs/2008.05673 (2020) - [i7]Shengyu Zhang, Ziqi Tan, Jin Yu, Zhou Zhao, Kun Kuang, Jie Liu, Jingren Zhou, Hongxia Yang, Fei Wu:
Poet: Product-oriented Video Captioner for E-commerce. CoRR abs/2008.06880 (2020) - [i6]Shengyu Zhang, Tan Jiang, Tan Wang, Kun Kuang, Zhou Zhao, Jianke Zhu, Jin Yu, Hongxia Yang, Fei Wu:
DeVLBert: Learning Deconfounded Visio-Linguistic Representations. CoRR abs/2008.06884 (2020) - [i5]Fengda Zhang, Kun Kuang, Zhaoyang You, Tao Shen, Jun Xiao, Yin Zhang, Chao Wu, Yueting Zhuang, Xiaolin Li:
Federated Unsupervised Representation Learning. CoRR abs/2010.08982 (2020) - [i4]Jun Wen, Changjian Shui, Kun Kuang, Junsong Yuan, Zenan Huang, Zhefeng Gong, Nenggan Zheng:
Interventional Domain Adaptation. CoRR abs/2011.03737 (2020)
2010 – 2019
- 2019
- [c8]Zhixiu Liu, Chengxi Zang, Kun Kuang, Hao Zou, Hu Zheng, Peng Cui:
Causation-Driven Visualizations for Insurance Recommendation. ICME Workshops 2019: 471-476 - [c7]Jianxin Ma, Peng Cui, Kun Kuang, Xin Wang, Wenwu Zhu:
Disentangled Graph Convolutional Networks. ICML 2019: 4212-4221 - [c6]Hao Zou, Kun Kuang, Boqi Chen, Peixuan Chen, Peng Cui:
Focused Context Balancing for Robust Offline Policy Evaluation. KDD 2019: 696-704 - [i3]Zheyan Shen, Peng Cui, Tong Zhang, Kun Kuang:
Stable Learning via Sample Reweighting. CoRR abs/1911.12580 (2019) - 2018
- [j1]Kun Kuang, Meng Jiang, Peng Cui, Hengliang Luo, Shiqiang Yang:
Effective Promotional Strategies Selection in Social Media: A Data-Driven Approach. IEEE Trans. Big Data 4(4): 487-501 (2018) - [c5]Kun Kuang, Peng Cui, Susan Athey, Ruoxuan Xiong, Bo Li:
Stable Prediction across Unknown Environments. KDD 2018: 1617-1626 - [c4]Zheyan Shen, Peng Cui, Kun Kuang, Bo Li, Peixuan Chen:
Causally Regularized Learning with Agnostic Data Selection Bias. ACM Multimedia 2018: 411-419 - [i2]Kun Kuang, Ruoxuan Xiong, Peng Cui, Susan Athey, Bo Li:
Stable Prediction across Unknown Environments. CoRR abs/1806.06270 (2018) - 2017
- [c3]Kun Kuang, Peng Cui, Bo Li, Meng Jiang, Shiqiang Yang, Fei Wang:
Treatment Effect Estimation with Data-Driven Variable Decomposition. AAAI 2017: 140-146 - [c2]Kun Kuang, Peng Cui, Bo Li, Meng Jiang, Shiqiang Yang:
Estimating Treatment Effect in the Wild via Differentiated Confounder Balancing. KDD 2017: 265-274 - [i1]Zheyan Shen, Peng Cui, Kun Kuang, Bo Li:
On Image Classification: Correlation v.s. Causality. CoRR abs/1708.06656 (2017) - 2016
- [c1]Kun Kuang, Meng Jiang, Peng Cui, Shiqiang Yang:
Steering Social Media Promotions with Effective Strategies. ICDM 2016: 985-990
Coauthor Index
[j34] [c112] [i100] [i98] [i97] [j32] [j30] [j29] [j27] [j26] [j25] [j24] [j22] [j21] [c110] [c108] [c107] [c106] [c103] [c102] [c101] [c99] [c98] [c96] [c94] [c93] [c92] [c90] [c88] [c83] [c82] [i96] [i95] [i94] [i93] [i91] [i90] [i89] [i88] [i87] [i84] [i82] [i81] [i79] [i78] [i77] [i76] [i74] [i73] [i72] [i69] [i67] [i66] [i65] [i64] [i62] [i60] [j20] [j19] [j18] [j17] [j16] [j15] [j14] [j13] [j12] [j10] [c80] [c79] [c77] [c74] [c73] [c72] [c71] [c70] [c69] [c64] [c62] [c59] [c58] [c57] [c56] [c55] [c54] [c52] [i58] [i56] [i55] [i54] [i52] [i51] [i50] [i49] [i48] [i47] [j9] [j8] [j7] [j6] [j5] [c51] [c50] [c49] [c48] [c47] [c46] [c44] [c43] [c42] [c41] [c39] [c38] [c37] [c36] [c35] [c34] [c33] [i45] [i43] [i42] [i41] [i40] [i38] [i37] [i36] [i35] [i33] [i32] [j4] [c31] [c30] [c29] [c28] [c27] [c26] [c24] [c23] [c21] [i31] [i30] [i29] [i28] [i26] [i24] [i22] [i21] [i20] [i19] [i18] [i17] [j2] [c18] [c16] [c14] [c12] [c11] [c10] [c9] [i15] [i13] [i12] [i10] [i7] [i6]
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2025-02-20 20:45 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
