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ORCIDQiang Liu 0006
Person information
- affiliation: Chinese Academy of Sciences, Institute of Automation, Center for Research on Intelligent Perception and Computing, Beijing, China
Other persons with the same name
- Qiang Liu — disambiguation page
- Qiang Liu 0001 — University of Texas at Austin, Department of Computer Science, TX, USA (and 2 more)
- Qiang Liu 0002 — Linköping University, Swedish e-Science Research Centre, Sweden
- Qiang Liu 0003
![[0000-0001-7531-4459]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0001-7531-4459")
— University of Essex, School of Computer Science and Electronic Engineering, Colchester, UK - Qiang Liu 0004 — National University of Defense Technology, College of Computer, Changsha, China
- Qiang Liu 0005 — Delft University of Technology, The Netherlands (and 1 more)
- Qiang Liu 0007 — Oak Ridge National Laboratory, Computer Science and Mathematics Division, TN, USA (and 1 more)
- Qiang Liu 0008 — Chinese Academy of Sciences, Institute of Computing Technology, Beijing, China (and 1 more)
- Qiang Liu 0009 — Joint Center for Global Change Studies, Beijing, China (and 2 more)
- Qiang Liu 0010 — Liaoning Shihua University, School of Information and Control Engineering, Fushun, China (and 1 more)
- Qiang Liu 0011 — Tianjin University, School of Microelectronics, China (and 1 more)
- Qiang Liu 0012 — Huaihai Institute of Technology, School of Electric Engineering, Lianyungang, China
- Qiang Liu 0013 — University of Nebraska-Lincoln, NE, USA (and 1 more)
- Qiang Liu 0014 — Beijing Jiaotong University, School of Computer and Information Technology, China
- Qiang Liu 0015 — Chinese University of Hong Kong
- Qiang Liu 0016 — University of Electronic Science and Technology of China, School of Communication and Information Engineering, Chengdu, China
- Qiang Liu 0017 — Hunan University, College of Electrical and Information Engineering, Changsha, China (and 1 more)
- Qiang Liu 0018 — Northeastern University, State Key Laboratory of Synthetical Automation for Process Industries, Shenyang, China
- Qiang Liu 0019 — University of Manchester, School of Engineering, UK
- Qiang Liu 0020 — Beijing Jiaotong University, Beijing Key Laboratory of Transportation Data Analysis and Mining, China
- Qiang Liu 0021 — Sichuan University, College of Electronics and Information Engineering, Chengdu, China
- Qiang Liu 0022 — University of Antwerp, Department of Biology, Belgium (and 1 more)
- Qiang Liu 0023 — Dalian University of Technology, School of Mechanical Engineering, China
- Qiang Liu 0024 — Beihang University, School of Mechanical Engineering and Automation, Beijing, China
- Qiang Liu 0025 — Shenzhen University, School of Mathematics and Statistics, China (and 1 more)
- Qiang Liu 0026 — Shandong University of Finance and Economics, Department of Network and Information Security, Jinan, China (and 1 more)
- Qiang Liu 0027 — Chinese Academy of Sciences, Changchun Institute of Optics, Fine Mechanics and Physics, China
- Qiang Liu 0028 — Harbin Institute of Technology, State Key Laboratory of Robotics and System, China
- Qiang Liu 0029 — Beijing Institute of Petrochemical Technology, Institute of Precision Electromagnetic Equipment and Advanced Measurement Technology, China (and 1 more)
- Qiang Liu 0030 — Beijing University of Posts and Telecommunications, School of Information and Communication, China
- Qiang Liu 0031 — Guangdong University of Technology, Guangzhou, China
- Qiang Liu 0032 — Hunan University of Technology, College of Computer Science, Intelligent Information Perception and Processing Technology Hunan Province Key Laboratory, Zhuzhou, China
- Qiang Liu 0033 — University of Pittsburgh, Department of Neurological Surgery, PA, USA
- Qiang Liu 0034 — EPFL, Lausanne, Vaud, Switzerland (and 1 more)
- Qiang Liu 0035 — Ningbo University, Faculty of Electrical Engineering and Computer Science, China
- Qiang Liu 0036 — Alibaba Group, China
- Qiang Liu 0037 — Beijing Normal University, College of Global Change and Earth System Science, Beijing, China
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2020 – today
- 2024
[j19]Yanqiao Zhu, Dingshuo Chen, Yuanqi Du, Yingze Wang, Qiang Liu, Shu Wu:
Molecular Contrastive Pretraining with Collaborative Featurizations. J. Chem. Inf. Model. 64(4): 1112-1122 (2024)- [j18]Yuwei Xia, Mengqi Zhang, Qiang Liu, Liang Wang, Shu Wu, Xiaoyu Zhang, Liang Wang:
MetaTKG++: Learning evolving factor enhanced meta-knowledge for temporal knowledge graph reasoning. Pattern Recognit. 155: 110629 (2024) - [j17]Liping Wang, Qiang Liu, Mengqi Zhang, Yaxuan Hu, Shu Wu, Liang Wang:
Stage-Aware Hierarchical Attentive Relational Network for Diagnosis Prediction. IEEE Trans. Knowl. Data Eng. 36(4): 1773-1784 (2024) - [j16]Junfei Wu, Weizhi Xu, Qiang Liu, Shu Wu, Liang Wang:
Adversarial Contrastive Learning for Evidence-Aware Fake News Detection With Graph Neural Networks. IEEE Trans. Knowl. Data Eng. 36(11): 5591-5604 (2024) - [j15]Liang Wang, Shu Wu, Qiang Liu, Yanqiao Zhu, Xiang Tao, Mengdi Zhang, Liang Wang:
Bi-Level Graph Structure Learning for Next POI Recommendation. IEEE Trans. Knowl. Data Eng. 36(11): 5695-5708 (2024) - [j14]Qiang Liu, Junfei Wu, Shu Wu, Liang Wang:
Out-of-Distribution Evidence-Aware Fake News Detection via Dual Adversarial Debiasing. IEEE Trans. Knowl. Data Eng. 36(11): 6801-6813 (2024) - [j13]Guofan Liu, Jinghao Zhang, Qiang Liu, Junfei Wu, Shu Wu, Liang Wang:
Uni-Modal Event-Agnostic Knowledge Distillation for Multimodal Fake News Detection. IEEE Trans. Knowl. Data Eng. 36(12): 9490-9503 (2024) - [j12]Zeyu Cui, Zekun Li, Shu Wu, Xiaoyu Zhang, Qiang Liu, Liang Wang, Mengmeng Ai:
DyGCN: Efficient Dynamic Graph Embedding With Graph Convolutional Network. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4635-4646 (2024) - [c63]Haisong Gong, Weizhi Xu, Shu Wu, Qiang Liu, Liang Wang:
Heterogeneous Graph Reasoning for Fact Checking over Texts and Tables. AAAI 2024: 100-108 - [c62]Haisong Gong, Qiang Liu, Shu Wu, Liang Wang:
Text-Guided Molecule Generation with Diffusion Language Model. AAAI 2024: 109-117 - [c61]Liang Wang, Xiang Tao, Qiang Liu, Shu Wu, Liang Wang:
Rethinking Graph Masked Autoencoders through Alignment and Uniformity. AAAI 2024: 15528-15536 - [c60]Jinghao Zhang, Yuting Liu, Qiang Liu, Shu Wu, Guibing Guo, Liang Wang:
Stealthy Attack on Large Language Model based Recommendation. ACL (1) 2024: 5839-5857 - [c59]Junfei Wu, Qiang Liu, Ding Wang, Jinghao Zhang, Shu Wu, Liang Wang, Tieniu Tan:
Logical Closed Loop: Uncovering Object Hallucinations in Large Vision-Language Models. ACL (Findings) 2024: 6944-6962 - [c58]Huanhuan Ma, Weizhi Xu, Yifan Wei, Liuji Chen, Liang Wang, Qiang Liu, Shu Wu:
EX-FEVER: A Dataset for Multi-hop Explainable Fact Verification. ACL (Findings) 2024: 9340-9353 - [c57]Yuwei Xia, Ding Wang, Qiang Liu, Liang Wang, Shu Wu, Xiaoyu Zhang:
Chain-of-History Reasoning for Temporal Knowledge Graph Forecasting. ACL (Findings) 2024: 16144-16159 - [c56]Xi Cheng, Liang Wang, Yunan Zeng, Qiang Liu:
CMG: A Causality-enhanced Multi-view Graph Model for Stock Trend Prediction. CIKM 2024: 3699-3703 - [c55]Jiajun Zhang, Zhixun Li, Qiang Liu, Shu Wu, Zilei Wang, Liang Wang:
Evolving to the Future: Unseen Event Adaptive Fake News Detection on Social Media. CIKM 2024: 4273-4277 - [c54]Mengqi Zhang, Xiaotian Ye, Qiang Liu, Pengjie Ren, Shu Wu, Zhumin Chen:
Knowledge Graph Enhanced Large Language Model Editing. EMNLP 2024: 22647-22662 - [c53]Huanhuan Ma, Jinghao Zhang, Qiang Liu, Shu Wu, Liang Wang:
Interpretable Multimodal Out-of-Context Detection with Soft Logic Regularization. ICASSP 2024: 4740-4744 - [c52]Zhao Tong, Qiang Liu, Haichao Shi, Yuwei Xia, Shu Wu, Xiaoyu Zhang:
Semantics Fusion of Hierarchical Transformers for Multimodal Named Entity Recognition. ICIC (LNAI 3) 2024: 414-426 - [c51]Zhixun Li, Yushun Dong, Qiang Liu, Jeffrey Xu Yu:
Rethinking Fair Graph Neural Networks from Re-balancing. KDD 2024: 1736-1745 - [c50]Xin Sun, Liang Wang, Qiang Liu, Shu Wu, Zilei Wang, Liang Wang:
DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization. KDD 2024: 2794-2805 - [c49]Jinghao Zhang, Guofan Liu, Qiang Liu, Shu Wu, Liang Wang:
Modality-Balanced Learning for Multimedia Recommendation. ACM Multimedia 2024: 7551-7560 - [c48]Liang Wang, Hao Fu, Shu Wu, Qiang Liu, Xuelei Tan, Fangsheng Huang, Mengdi Zhang, Wei Wu:
CAMLO: Cross-Attentive Multi-View Network for Long-Term Origin-Destination Flow Prediction. SDM 2024: 454-462 - [c47]Xiang Tao, Liang Wang, Qiang Liu, Shu Wu, Liang Wang:
Semantic Evolvement Enhanced Graph Autoencoder for Rumor Detection. WWW 2024: 4150-4159 - [i74]Qiang Liu, Xiang Tao, Junfei Wu, Shu Wu, Liang Wang:
Can Large Language Models Detect Rumors on Social Media? CoRR abs/2402.03916 (2024) - [i73]Liang Wang, Xiang Tao, Qiang Liu, Shu Wu, Liang Wang:
Rethinking Graph Masked Autoencoders through Alignment and Uniformity. CoRR abs/2402.07225 (2024) - [i72]Junfei Wu, Qiang Liu, Ding Wang, Jinghao Zhang, Shu Wu, Liang Wang, Tieniu Tan:
Logical Closed Loop: Uncovering Object Hallucinations in Large Vision-Language Models. CoRR abs/2402.11622 (2024) - [i71]Haisong Gong, Weizhi Xu, Shu Wu, Qiang Liu, Liang Wang:
Heterogeneous Graph Reasoning for Fact Checking over Texts and Tables. CoRR abs/2402.13028 (2024) - [i70]Haisong Gong, Qiang Liu, Shu Wu, Liang Wang:
Text-Guided Molecule Generation with Diffusion Language Model. CoRR abs/2402.13040 (2024) - [i69]Mengqi Zhang, Xiaotian Ye, Qiang Liu, Pengjie Ren, Shu Wu, Zhumin Chen:
Knowledge Graph Enhanced Large Language Model Editing. CoRR abs/2402.13593 (2024) - [i68]Yuwei Xia, Ding Wang, Qiang Liu, Liang Wang, Shu Wu, Xiaoyu Zhang:
Enhancing Temporal Knowledge Graph Forecasting with Large Language Models via Chain-of-History Reasoning. CoRR abs/2402.14382 (2024) - [i67]Jinghao Zhang, Yuting Liu, Qiang Liu, Shu Wu, Guibing Guo, Liang Wang:
Stealthy Attack on Large Language Model based Recommendation. CoRR abs/2402.14836 (2024) - [i66]Jiajun Zhang, Zhixun Li, Qiang Liu, Shu Wu, Liang Wang:
Evolving to the Future: Unseen Event Adaptive Fake News Detection on Social Media. CoRR abs/2403.00037 (2024) - [i65]Han Huang, Haitian Zhong, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan:
KEBench: A Benchmark on Knowledge Editing for Large Vision-Language Models. CoRR abs/2403.07350 (2024) - [i64]Jiaqi Guan, Xiangxin Zhou, Yuwei Yang, Yu Bao, Jian Peng, Jianzhu Ma, Qiang Liu, Liang Wang, Quanquan Gu:
DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design. CoRR abs/2403.07902 (2024) - [i63]Yuting Liu, Yizhou Dang, Yuliang Liang, Qiang Liu, Guibing Guo, Jianzhe Zhao, Xingwei Wang:
Towards Unified Modeling for Positive and Negative Preferences in Sign-Aware Recommendation. CoRR abs/2403.08246 (2024) - [i62]Yi Xiao, Xiangxin Zhou, Qiang Liu, Liang Wang:
Bridging Text and Molecule: A Survey on Multimodal Frameworks for Molecule. CoRR abs/2403.13830 (2024) - [i61]Xiang Tao, Mingqing Zhang, Qiang Liu, Shu Wu, Liang Wang:
Out-of-distribution Rumor Detection via Test-Time Adaptation. CoRR abs/2403.17735 (2024) - [i60]Xiang Tao, Liang Wang, Qiang Liu, Shu Wu, Liang Wang:
Semantic Evolvement Enhanced Graph Autoencoder for Rumor Detection. CoRR abs/2404.16076 (2024) - [i59]Huanhuan Ma, Jinghao Zhang, Qiang Liu, Shu Wu, Liang Wang:
Interpretable Multimodal Out-of-context Detection with Soft Logic Regularization. CoRR abs/2406.04756 (2024) - [i58]Zhixun Li, Yushun Dong, Qiang Liu, Jeffrey Xu Yu:
Rethinking Fair Graph Neural Networks from Re-balancing. CoRR abs/2407.11624 (2024) - [i57]Haisong Gong, Huanhuan Ma, Qiang Liu, Shu Wu, Liang Wang:
Navigating the Noisy Crowd: Finding Key Information for Claim Verification. CoRR abs/2407.12425 (2024) - [i56]Xin Sun, Liang Wang, Qiang Liu, Shu Wu, Zilei Wang, Liang Wang:
DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization. CoRR abs/2408.04400 (2024) - [i55]Yuting Liu, Jinghao Zhang, Yizhou Dang, Yuliang Liang, Qiang Liu, Guibing Guo, Jianzhe Zhao, Xingwei Wang:
CoRA: Collaborative Information Perception by Large Language Model's Weights for Recommendation. CoRR abs/2408.10645 (2024) - [i54]Mengqi Zhang, Bowen Fang, Qiang Liu, Pengjie Ren, Shu Wu, Zhumin Chen, Liang Wang:
Enhancing Multi-hop Reasoning through Knowledge Erasure in Large Language Model Editing. CoRR abs/2408.12456 (2024) - [i53]Dingshuo Chen, Zhixun Li, Yuyan Ni, Guibin Zhang, Ding Wang, Qiang Liu, Shu Wu, Jeffrey Xu Yu, Liang Wang:
Beyond Efficiency: Molecular Data Pruning for Enhanced Generalization. CoRR abs/2409.01081 (2024) - [i52]Mengqi Zhang, Xiaotian Ye, Qiang Liu, Pengjie Ren, Shu Wu, Zhumin Chen:
Uncovering Overfitting in Large Language Model Editing. CoRR abs/2410.07819 (2024) - [i51]Liang Wang, Qiang Liu, Shaozhen Liu, Xin Sun, Shu Wu, Liang Wang:
Pin-Tuning: Parameter-Efficient In-Context Tuning for Few-Shot Molecular Property Prediction. CoRR abs/2411.01158 (2024) - [i50]Liang Wang, Shu Wu, Qiang Liu, Yanqiao Zhu, Xiang Tao, Mengdi Zhang, Liang Wang:
Bi-Level Graph Structure Learning for Next POI Recommendation. CoRR abs/2411.01169 (2024) - 2023
- [j11]Chang Zhang, Xiangzhu Meng, Qiang Liu, Shu Wu, Liang Wang, Huansheng Ning:
FedBrain: A robust multi-site brain network analysis framework based on federated learning for brain disease diagnosis. Neurocomputing 559: 126791 (2023) - [j10]Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu:
Unsupervised Graph Representation Learning with Cluster-aware Self-training and Refining. ACM Trans. Intell. Syst. Technol. 14(5): 82:1-82:21 (2023) - [j9]Mengqi Zhang, Shu Wu, Xueli Yu, Qiang Liu, Liang Wang:
Dynamic Graph Neural Networks for Sequential Recommendation. IEEE Trans. Knowl. Data Eng. 35(5): 4741-4753 (2023) - [j8]Qiang Liu, Yingtao Luo, Shu Wu, Zhen Zhang, Xiangnan Yue, Hong Jin, Liang Wang:
RMT-Net: Reject-Aware Multi-Task Network for Modeling Missing-Not-At-Random Data in Financial Credit Scoring. IEEE Trans. Knowl. Data Eng. 35(7): 7427-7439 (2023) - [j7]Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Mengqi Zhang, Shu Wu, Liang Wang:
Latent Structure Mining With Contrastive Modality Fusion for Multimedia Recommendation. IEEE Trans. Knowl. Data Eng. 35(9): 9154-9167 (2023) - [c46]Weizhi Xu, Qiang Liu, Shu Wu, Liang Wang:
Counterfactual Debiasing for Fact Verification. ACL (1) 2023: 6777-6789 - [c45]Mengqi Zhang, Yuwei Xia, Qiang Liu, Shu Wu, Liang Wang:
Learning Latent Relations for Temporal Knowledge Graph Reasoning. ACL (1) 2023: 12617-12631 - [c44]Zewen Long, Liang Wang, Qiang Liu, Shu Wu:
Personalized Interest Sustainability Modeling for Sequential POI Recommendation. CIKM 2023: 4145-4149 - [c43]Xin Sun, Qiang Liu, Shu Wu, Zilei Wang, Liang Wang:
Noise-Robust Semi-Supervised Learning for Distantly Supervised Relation Extraction. EMNLP (Findings) 2023: 13145-13157 - [c42]Jiaqi Guan, Xiangxin Zhou, Yuwei Yang, Yu Bao, Jian Peng, Jianzhu Ma, Qiang Liu, Liang Wang, Quanquan Gu:
DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design. ICML 2023: 11827-11846 - [c41]Yingtao Luo, Qiang Liu, Yuntian Chen, Wenbo Hu, Tian Tian, Jun Zhu:
Physics-Guided Discovery of Highly Nonlinear Parametric Partial Differential Equations. KDD 2023: 1595-1607 - [c40]Dingshuo Chen, Yanqiao Zhu, Jieyu Zhang, Yuanqi Du, Zhixun Li, Qiang Liu, Shu Wu, Liang Wang:
Uncovering Neural Scaling Laws in Molecular Representation Learning. NeurIPS 2023 - [c39]Zhixun Li, Xin Sun, Yifan Luo, Yanqiao Zhu, Dingshuo Chen, Yingtao Luo, Xiangxin Zhou, Qiang Liu, Shu Wu, Liang Wang, Jeffrey Xu Yu:
GSLB: The Graph Structure Learning Benchmark. NeurIPS 2023 - [c38]Jinghao Zhang, Qiang Liu, Shu Wu, Liang Wang:
Mining Stable Preferences: Adaptive Modality Decorrelation for Multimedia Recommendation. SIGIR 2023: 443-452 - [c37]Mengqi Zhang, Yuwei Xia, Qiang Liu, Shu Wu, Liang Wang:
Learning Long- and Short-term Representations for Temporal Knowledge Graph Reasoning. WWW 2023: 2412-2422 - [i49]Yuwei Xia, Mengqi Zhang, Qiang Liu, Shu Wu, Xiaoyu Zhang:
MetaTKG: Learning Evolutionary Meta-Knowledge for Temporal Knowledge Graph Reasoning. CoRR abs/2302.00893 (2023) - [i48]Wenbo Hu, Xin Sun, Qiang Liu, Shu Wu:
Uncertainty Calibration for Counterfactual Propensity Estimation in Recommendation. CoRR abs/2303.12973 (2023) - [i47]Qiang Liu, Zhaocheng Liu, Zhenxi Zhu, Shu Wu, Liang Wang:
Deep Stable Multi-Interest Learning for Out-of-distribution Sequential Recommendation. CoRR abs/2304.05615 (2023) - [i46]Qiang Liu, Junfei Wu, Shu Wu, Liang Wang:
Out-of-distribution Evidence-aware Fake News Detection via Dual Adversarial Debiasing. CoRR abs/2304.12888 (2023) - [i45]Jinghao Zhang, Qiang Liu, Shu Wu, Liang Wang:
Mining Stable Preferences: Adaptive Modality Decorrelation for Multimedia Recommendation. CoRR abs/2306.14179 (2023) - [i44]Xiangzhu Meng, Wei Wei, Qiang Liu, Shu Wu, Liang Wang:
TiBGL: Template-induced Brain Graph Learning for Functional Neuroimaging Analysis. CoRR abs/2309.07947 (2023) - [i43]Xiangzhu Meng, Wei Wei, Qiang Liu, Shu Wu, Liang Wang:
TCGF: A unified tensorized consensus graph framework for multi-view representation learning. CoRR abs/2309.09987 (2023) - [i42]Dingshuo Chen, Yanqiao Zhu, Jieyu Zhang, Yuanqi Du, Zhixun Li, Qiang Liu, Shu Wu, Liang Wang:
Uncovering Neural Scaling Laws in Molecular Representation Learning. CoRR abs/2309.15123 (2023) - [i41]Zhixun Li, Liang Wang, Xin Sun, Yifan Luo, Yanqiao Zhu, Dingshuo Chen, Yingtao Luo, Xiangxin Zhou, Qiang Liu, Shu Wu, Liang Wang, Jeffrey Xu Yu:
GSLB: The Graph Structure Learning Benchmark. CoRR abs/2310.05174 (2023) - [i40]Huanhuan Ma, Weizhi Xu, Yifan Wei, Liuji Chen, Liang Wang, Qiang Liu, Shu Wu, Liang Wang:
EX-FEVER: A Dataset for Multi-hop Explainable Fact Verification. CoRR abs/2310.09754 (2023) - [i39]Yuting Liu, Enneng Yang, Yizhou Dang, Guibing Guo, Qiang Liu, Yuliang Liang, Linying Jiang, Xingwei Wang:
ID Embedding as Subtle Features of Content and Structure for Multimodal Recommendation. CoRR abs/2311.05956 (2023) - 2022
- [c36]Chenyang Su, Qiang Liu, Liang Wang:
Uncertainty Estimation Based Doubly Robust Learning for Debiasing Recommendation. CCIS 2022: 696-701 - [c35]Fenyu Hu, Zeyu Cui, Shu Wu, Qiang Liu, Jinlin Wu, Liang Wang, Tieniu Tan:
Second-Order Global Attention Networks for Graph Classification and Regression. CICAI (2) 2022: 496-507 - [c34]Mengqi Zhang, Yanqiao Zhu, Qiang Liu, Shu Wu, Liang Wang:
Deep Contrastive Multiview Network Embedding. CIKM 2022: 4692-4696 - [c33]Liping Wang, Qiang Liu, Huanhuan Ma, Shu Wu, Liang Wang:
Multi-Cause Learning for Diagnosis Prediction. DMBD (1) 2022: 320-332 - [c32]Yuwei Xia, Mengqi Zhang, Qiang Liu, Shu Wu, Xiaoyu Zhang:
MetaTKG: Learning Evolutionary Meta-Knowledge for Temporal Knowledge Graph Reasoning. EMNLP 2022: 7230-7240 - [c31]Zhixun Li, Dingshuo Chen, Qiang Liu, Shu Wu:
The Devil is in the Conflict: Disentangled Information Graph Neural Networks for Fraud Detection. ICDM 2022: 1059-1064 - [c30]Yingtao Luo, Zhaocheng Liu, Qiang Liu:
Deep Stable Representation Learning on Electronic Health Records. ICDM 2022: 1077-1082 - [c29]Fenyu Hu, Liping Wang, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan:
GraphDIVE: Graph Classification by Mixture of Diverse Experts. IJCAI 2022: 2080-2086 - [c28]Yanqiao Zhu, Yuanqi Du, Yinkai Wang, Yichen Xu, Jieyu Zhang, Qiang Liu, Shu Wu:
A Survey on Deep Graph Generation: Methods and Applications. LoG 2022: 47 - [c27]Yabo Chu, Enneng Yang, Qiang Liu, Yuting Liu, Linying Jiang, Guibing Guo:
Bi-directional Contrastive Distillation for Multi-behavior Recommendation. ECML/PKDD (1) 2022: 491-507 - [c26]Yanqiao Zhu, Yichen Xu, Hejie Cui, Carl Yang, Qiang Liu, Shu Wu:
Structure-Enhanced Heterogeneous Graph Contrastive Learning. SDM 2022: 82-90 - [c25]Junfei Wu, Qiang Liu, Weizhi Xu, Shu Wu:
Bias Mitigation for Evidence-aware Fake News Detection by Causal Intervention. SIGIR 2022: 2308-2313 - [c24]Weizhi Xu, Junfei Wu, Qiang Liu, Shu Wu, Liang Wang:
Evidence-aware Fake News Detection with Graph Neural Networks. WWW 2022: 2501-2510 - [i38]Weizhi Xu, Junfei Wu, Qiang Liu, Shu Wu, Liang Wang:
Mining Fine-grained Semantics via Graph Neural Networks for Evidence-based Fake News Detection. CoRR abs/2201.06885 (2022) - [i37]Yanqiao Zhu, Yuanqi Du, Yinkai Wang, Yichen Xu, Jieyu Zhang, Qiang Liu, Shu Wu:
A Survey on Deep Graph Generation: Methods and Applications. CoRR abs/2203.06714 (2022) - [i36]Yi Guo, Zhaocheng Liu, Jianchao Tan, Chao Liao, Daqing Chang, Qiang Liu, Sen Yang, Ji Liu, Dongying Kong, Zhi Chen, Chengru Song:
LPFS: Learnable Polarizing Feature Selection for Click-Through Rate Prediction. CoRR abs/2206.00267 (2022) - [i35]Qiang Liu, Yingtao Luo, Shu Wu, Zhen Zhang, Xiangnan Yue, Hong Jin, Liang Wang:
RMT-Net: Reject-aware Multi-Task Network for Modeling Missing-not-at-random Data in Financial Credit Scoring. CoRR abs/2206.00568 (2022) - [i34]Zhaocheng Liu, Yingtao Luo, Di Zeng, Qiang Liu, Daqing Chang, Dongying Kong, Zhi Chen:
Improving Multi-Interest Network with Stable Learning. CoRR abs/2207.07910 (2022) - [i33]Yingtao Luo, Zhaocheng Liu, Qiang Liu:
Deep Stable Representation Learning on Electronic Health Records. CoRR abs/2209.01321 (2022) - [i32]Yanqiao Zhu, Dingshuo Chen, Yuanqi Du, Yingze Wang, Qiang Liu, Shu Wu:
Improving Molecular Pretraining with Complementary Featurizations. CoRR abs/2209.15101 (2022) - [i31]Junfei Wu, Weizhi Xu, Qiang Liu, Shu Wu, Liang Wang:
Adversarial Contrastive Learning for Evidence-aware Fake News Detection with Graph Neural Networks. CoRR abs/2210.05498 (2022) - [i30]Zhixun Li, Dingshuo Chen, Qiang Liu, Shu Wu:
The Devil is in the Conflict: Disentangled Information Graph Neural Networks for Fraud Detection. CoRR abs/2210.12384 (2022) - 2021
- [j6]Zeyu Cui, Feng Yu, Shu Wu, Qiang Liu, Liang Wang:
Disentangled Item Representation for Recommender Systems. ACM Trans. Intell. Syst. Technol. 12(2): 20:1-20:20 (2021) - [c23]Qiang Liu, Haoli Zhang, Zhaocheng Liu:
Simplifying Graph Convolutional Networks as Matrix Factorization. APWeb/WAIM (1) 2021: 35-43 - [c22]Qiang Liu, Zhaocheng Liu, Haoli Zhang, Yuntian Chen, Jun Zhu:
Mining Cross Features for Financial Credit Risk Assessment. CIKM 2021: 1069-1078 - [c21]Qiang Liu, Yanqiao Zhu, Zhaocheng Liu, Yufeng Zhang, Shu Wu:
Deep Active Learning for Text Classification with Diverse Interpretations. CIKM 2021: 3263-3267 - [c20]Yichen Xu, Yanqiao Zhu, Feng Yu, Qiang Liu, Shu Wu:
Disentangled Self-Attentive Neural Networks for Click-Through Rate Prediction. CIKM 2021: 3553-3557 - [c19]Qilong Yan, Yufeng Zhang, Qiang Liu, Shu Wu, Liang Wang:
Relation-aware Heterogeneous Graph for User Profiling. CIKM 2021: 3573-3577 - [c18]Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Shu Wu, Shuhui Wang, Liang Wang:
Mining Latent Structures for Multimedia Recommendation. ACM Multimedia 2021: 3872-3880 - [c17]Yanqiao Zhu, Yichen Xu, Qiang Liu, Shu Wu:
An Empirical Study of Graph Contrastive Learning. NeurIPS Datasets and Benchmarks 2021 - [c16]Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang:
Graph Contrastive Learning with Adaptive Augmentation. WWW 2021: 2069-2080 - [c15]Yingtao Luo, Qiang Liu, Zhaocheng Liu:
STAN: Spatio-Temporal Attention Network for Next Location Recommendation. WWW 2021: 2177-2185 - [i29]Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang:
Disentangled Self-Attentive Neural Networks for Click-Through Rate Prediction. CoRR abs/2101.03654 (2021) - [i28]Yingtao Luo, Qiang Liu, Zhaocheng Liu:
STAN: Spatio-Temporal Attention Network for Next Location Recommendation. CoRR abs/2102.04095 (2021) - [i27]Qiang Liu, Zhaocheng Liu, Haoli Zhang, Yuntian Chen, Jun Zhu:
DNN2LR: Automatic Feature Crossing for Credit Scoring. CoRR abs/2102.12036 (2021) - [i26]Yanqiao Zhu, Weizhi Xu, Jinghao Zhang, Qiang Liu, Shu Wu, Liang Wang:
Deep Graph Structure Learning for Robust Representations: A Survey. CoRR abs/2103.03036 (2021) - [i25]Zeyu Cui, Zekun Li, Shu Wu, Xiaoyu Zhang, Qiang Liu, Liang Wang, Mengmeng Ai:
DyGCN: Dynamic Graph Embedding with Graph Convolutional Network. CoRR abs/2104.02962 (2021) - [i24]Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Shu Wu, Shuhui Wang, Liang Wang:
Mining Latent Structures for Multimedia Recommendation. CoRR abs/2104.09036 (2021) - [i23]Yingtao Luo, Qiang Liu, Yuntian Chen, Wenbo Hu, Jun Zhu:
KO-PDE: Kernel Optimized Discovery of Partial Differential Equations with Varying Coefficients. CoRR abs/2106.01078 (2021) - [i22]Yuntian Chen, Yingtao Luo, Qiang Liu, Hao Xu, Dongxiao Zhang:
Any equation is a forest: Symbolic genetic algorithm for discovering open-form partial differential equations (SGA-PDE). CoRR abs/2106.11927 (2021) - [i21]Qiang Liu, Yanqiao Zhu, Zhaocheng Liu, Yufeng Zhang, Shu Wu:
Deep Active Learning for Text Classification with Diverse Interpretations. CoRR abs/2108.10687 (2021) - [i20]Yanqiao Zhu, Yichen Xu, Hejie Cui, Carl Yang, Qiang Liu, Shu Wu:
Structure-Aware Hard Negative Mining for Heterogeneous Graph Contrastive Learning. CoRR abs/2108.13886 (2021) - [i19]Yanqiao Zhu, Yichen Xu, Qiang Liu, Shu Wu:
An Empirical Study of Graph Contrastive Learning. CoRR abs/2109.01116 (2021) - [i18]Qilong Yan, Yufeng Zhang, Qiang Liu, Shu Wu, Liang Wang:
Relation-aware Heterogeneous Graph for User Profiling. CoRR abs/2110.07181 (2021) - [i17]Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Mengqi Zhang, Shu Wu, Liang Wang:
Latent Structures Mining with Contrastive Modality Fusion for Multimedia Recommendation. CoRR abs/2111.00678 (2021) - 2020
- [j5]Qiang Cui, Shu Wu, Qiang Liu, Wen Zhong, Liang Wang:
MV-RNN: A Multi-View Recurrent Neural Network for Sequential Recommendation. IEEE Trans. Knowl. Data Eng. 32(2): 317-331 (2020) - [c14]Feng Yu, Zhaocheng Liu, Qiang Liu, Haoli Zhang, Shu Wu, Liang Wang:
Deep Interaction Machine: A Simple but Effective Model for High-order Feature Interactions. CIKM 2020: 2285-2288 - [c13]Shu Wu, Feng Yu, Xueli Yu, Qiang Liu, Liang Wang, Tieniu Tan, Jie Shao, Fan Huang:
TFNet: Multi-Semantic Feature Interaction for CTR Prediction. SIGIR 2020: 1885-1888 - [c12]Feng Yu, Yanqiao Zhu, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan:
TAGNN: Target Attentive Graph Neural Networks for Session-based Recommendation. SIGIR 2020: 1921-1924 - [i16]Qiang Liu, Zhaocheng Liu, Haoli Zhang:
An Empirical Study on Feature Discretization. CoRR abs/2004.12602 (2020) - [i15]Feng Yu, Yanqiao Zhu, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan:
TAGNN: Target Attentive Graph Neural Networks for Session-based Recommendation. CoRR abs/2005.02844 (2020) - [i14]Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang:
Deep Graph Contrastive Representation Learning. CoRR abs/2006.04131 (2020) - [i13]Shu Wu, Feng Yu, Xueli Yu, Qiang Liu, Liang Wang, Tieniu Tan, Jie Shao, Fan Huang:
TFNet: Multi-Semantic Feature Interaction for CTR Prediction. CoRR abs/2006.15939 (2020) - [i12]Qiang Liu, Haoli Zhang, Zhaocheng Liu:
Simplification of Graph Convolutional Networks: A Matrix Factorization-based Perspective. CoRR abs/2007.09036 (2020) - [i11]Qiang Liu, Zhaocheng Liu, Xiaofang Zhu, Yeliang Xiu, Jun Zhu:
Deep Active Learning by Model Interpretability. CoRR abs/2007.12100 (2020) - [i10]Zeyu Cui, Feng Yu, Shu Wu, Qiang Liu, Liang Wang:
Disentangled Item Representation for Recommender Systems. CoRR abs/2008.07178 (2020) - [i9]Zhaocheng Liu, Qiang Liu, Haoli Zhang, Yuntian Chen:
DNN2LR: Interpretation-inspired Feature Crossing for Real-world Tabular Data. CoRR abs/2008.09775 (2020) - [i8]Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang:
Graph Contrastive Learning with Adaptive Augmentation. CoRR abs/2010.14945 (2020) - [i7]Yanqiao Zhu, Weizhi Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang:
Deep Active Graph Representation Learning. CoRR abs/2010.16091 (2020)
2010 – 2019
- 2019
- [j4]Feng Yu, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan:
Attention-based convolutional approach for misinformation identification from massive and noisy microblog posts. Comput. Secur. 83: 106-121 (2019) - [c11]Jingyi Wang, Qiang Liu, Zhaocheng Liu, Shu Wu:
Towards Accurate and Interpretable Sequential Prediction: A CNN & Attention-Based Feature Extractor. CIKM 2019: 1703-1712 - [i6]Qiang Liu, Shu Wu, Liang Wang:
Learning Preferences and Demands in Visual Recommendation. CoRR abs/1911.04229 (2019) - 2018
- [j3]Qiang Liu, Feng Yu, Shu Wu, Liang Wang:
Mining Significant Microblogs for Misinformation Identification: An Attention-Based Approach. ACM Trans. Intell. Syst. Technol. 9(5): 50:1-50:20 (2018) - 2017
- [b1]Shu Wu, Qiang Liu, Liang Wang, Tieniu Tan:
Context-Aware Collaborative Prediction. Springer Briefs in Computer Science, Springer 2017, ISBN 978-981-10-5372-6, pp. 1-69 - [j2]Qiang Liu, Shu Wu, Liang Wang:
Multi-Behavioral Sequential Prediction with Recurrent Log-Bilinear Model. IEEE Trans. Knowl. Data Eng. 29(6): 1254-1267 (2017) - [c10]Feng Yu, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan:
A Convolutional Approach for Misinformation Identification. IJCAI 2017: 3901-3907 - [c9]Qiang Liu, Shu Wu, Liang Wang:
DeepStyle: Learning User Preferences for Visual Recommendation. SIGIR 2017: 841-844 - [i5]Qiang Liu, Feng Yu, Shu Wu, Liang Wang:
Mining Significant Microblogs for Misinformation Identification: An Attention-based Approach. CoRR abs/1706.06314 (2017) - 2016
- [j1]Shu Wu, Qiang Liu, Liang Wang, Tieniu Tan:
Contextual Operation for Recommender Systems. IEEE Trans. Knowl. Data Eng. 28(8): 2000-2012 (2016) - [c8]Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan:
Predicting the Next Location: A Recurrent Model with Spatial and Temporal Contexts. AAAI 2016: 194-200 - [c7]Shu Wu, Qiang Liu, Ping Bai, Liang Wang, Tieniu Tan:
SAPE: A System for Situation-Aware Public Security Evaluation. AAAI 2016: 4401-4402 - [c6]Shu Wu, Qiang Liu, Yong Liu, Liang Wang, Tieniu Tan:
Information Credibility Evaluation on Social Media. AAAI 2016: 4403-4404 - [c5]Qiang Liu, Shu Wu, Diyi Wang, Zhaokang Li, Liang Wang:
Context-Aware Sequential Recommendation. ICDM 2016: 1053-1058 - [c4]Feng Yu, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan:
A Dynamic Recurrent Model for Next Basket Recommendation. SIGIR 2016: 729-732 - [i4]Qiang Liu, Shu Wu, Liang Wang:
Multi-behavioral Sequential Prediction for Collaborative Filtering. CoRR abs/1608.07102 (2016) - [i3]Qiang Liu, Shu Wu, Diyi Wang, Zhaokang Li, Liang Wang:
Context-aware Sequential Recommendation. CoRR abs/1609.05787 (2016) - [i2]Qiang Liu, Shu Wu, Feng Yu, Liang Wang, Tieniu Tan:
ICE: Information Credibility Evaluation on Social Media via Representation Learning. CoRR abs/1609.09226 (2016) - [i1]Qiang Cui, Shu Wu, Qiang Liu, Liang Wang:
A Visual and Textual Recurrent Neural Network for Sequential Prediction. CoRR abs/1611.06668 (2016) - 2015
- [c3]Qiang Liu, Shu Wu, Liang Wang:
COT: Contextual Operating Tensor for Context-Aware Recommender Systems. AAAI 2015: 203-209 - [c2]Qiang Liu, Shu Wu, Liang Wang:
Collaborative Prediction for Multi-entity Interaction With Hierarchical Representation. CIKM 2015: 613-622 - [c1]Qiang Liu, Feng Yu, Shu Wu, Liang Wang:
A Convolutional Click Prediction Model. CIKM 2015: 1743-1746
Coauthor Index
[j18] [j17] [j16] [j15] [j14] [j13] [j12] [c62] [c61] [c60] [c59] [c55] [c53] [c50] [c49] [c48] [c47] [i74] [i73] [i72] [i68] [i67] [i66] [i65] [i64] [i62] [i61] [i60] [i59] [i57] [i56] [i54] [i51] [i50] [j11] [j9] [j8] [j7] [c46] [c45] [c43] [c42] [c39] [c38] [c37] [i47] [i46] [i45] [i44] [i43] [i42] [i41] [i40] [c36] [c35] [c34] [c33] [c29] [c24] [i38] [i35] [i31] [j6] [c19] [c18] [c16] [i29] [i26] [i25] [i24] [i18] [i17] [j5] [c14] [c13] [c12] [i15] [i14] [i13] [i10] [i8] [i7] [j4] [i6] [j3] [b1] [j2] [c10] [c9] [i5] [j1] [c8] [c7] [c6] [c5] [c4] [i4] [i3] [i2] [i1] [c3] [c2] [c1]
[j19] [j18] [j17] [j16] [j15] [j14] [j13] [j12] [c63] [c62] [c61] [c60] [c59] [c58] [c57] [c55] [c54] [c53] [c52] [c50] [c49] [c48] [c47] [i74] [i73] [i72] [i71] [i70] [i69] [i68] [i67] [i66] [i65] [i61] [i60] [i59] [i57] [i56] [i54] [i53] [i52] [i51] [i50] [j11] [j10] [j9] [j8] [j7] [c46] [c45] [c44] [c43] [c40] [c39] [c38] [c37] [i49] [i48] [i47] [i46] [i45] [i44] [i43] [i42] [i41] [i40] [c35] [c34] [c33] [c32] [c31] [c29] [c28] [c26] [c25] [c24] [i38] [i37] [i35] [i32] [i31] [i30] [j6] [c21] [c20] [c19] [c18] [c17] [c16] [i29] [i26] [i25] [i24] [i21] [i20] [i19] [i18] [i17] [j5] [c14] [c13] [c12] [i15] [i14] [i13] [i10] [i8] [i7] [j4] [c11] [i6] [j3] [b1] [j2] [c10] [c9] [i5] [j1] [c8] [c7] [c6] [c5] [c4] [i4] [i3] [i2] [i1] [c3] [c2] [c1]
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