Qiang Liu

According to our database, Qiang Liu authored at least 126 papers between 2015 and 2024.

Collaborative distances:

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

2024

Adversarial Contrastive Learning for Evidence-Aware Fake News Detection With Graph Neural Networks.

Junfei Wu, Weizhi Xu, Qiang Liu, Shu Wu, Liang Wang

IEEE Trans. Knowl. Data Eng., November, 2024

Bi-Level Graph Structure Learning for Next POI Recommendation.

Liang Wang, Shu Wu, Qiang Liu, Yanqiao Zhu, Xiang Tao, Mengdi Zhang, Liang Wang

IEEE Trans. Knowl. Data Eng., November, 2024

Out-of-Distribution Evidence-Aware Fake News Detection via Dual Adversarial Debiasing.

Qiang Liu, Junfei Wu, Shu Wu, Liang Wang

IEEE Trans. Knowl. Data Eng., November, 2024

DyGCN: Efficient Dynamic Graph Embedding With Graph Convolutional Network.

Zeyu Cui, Zekun Li, Shu Wu, Xiaoyu Zhang, Qiang Liu, Liang Wang, Mengmeng Ai

IEEE Trans. Neural Networks Learn. Syst., April, 2024

Stage-Aware Hierarchical Attentive Relational Network for Diagnosis Prediction.

Liping Wang, Qiang Liu, Mengqi Zhang, Yaxuan Hu, Shu Wu, Liang Wang

IEEE Trans. Knowl. Data Eng., April, 2024

Molecular Contrastive Pretraining with Collaborative Featurizations.

Yanqiao Zhu, Dingshuo Chen, Yuanqi Du, Yingze Wang, Qiang Liu, Shu Wu

J. Chem. Inf. Model., February, 2024

MetaTKG++: Learning evolving factor enhanced meta-knowledge for temporal knowledge graph reasoning.

Yuwei Xia, Mengqi Zhang, Qiang Liu, Liang Wang, Shu Wu, Xiaoyu Zhang, Liang Wang

Pattern Recognit., 2024

Uncovering Overfitting in Large Language Model Editing.

Mengqi Zhang, Xiaotian Ye, Qiang Liu, Pengjie Ren, Shu Wu, Zhumin Chen

CoRR, 2024

Beyond Efficiency: Molecular Data Pruning for Enhanced Generalization.

Dingshuo Chen, Zhixun Li, Yuyan Ni, Guibin Zhang, Ding Wang, Qiang Liu, Shu Wu, Jeffrey Xu Yu, Liang Wang

CoRR, 2024

Enhancing Multi-hop Reasoning through Knowledge Erasure in Large Language Model Editing.

Mengqi Zhang, Bowen Fang, Qiang Liu, Pengjie Ren, Shu Wu, Zhumin Chen, Liang Wang

CoRR, 2024

CoRA: Collaborative Information Perception by Large Language Model's Weights for Recommendation.

Yuting Liu, Jinghao Zhang, Yizhou Dang, Yuliang Liang, Qiang Liu, Guibing Guo, Jianzhe Zhao, Xingwei Wang

CoRR, 2024

Navigating the Noisy Crowd: Finding Key Information for Claim Verification.

Haisong Gong, Huanhuan Ma, Qiang Liu, Shu Wu, Liang Wang

CoRR, 2024

Out-of-distribution Rumor Detection via Test-Time Adaptation.

Xiang Tao, Mingqing Zhang, Qiang Liu, Shu Wu, Liang Wang

CoRR, 2024

Bridging Text and Molecule: A Survey on Multimodal Frameworks for Molecule.

Yi Xiao, Xiangxin Zhou, Qiang Liu, Liang Wang

CoRR, 2024

Towards Unified Modeling for Positive and Negative Preferences in Sign-Aware Recommendation.

Yuting Liu, Yizhou Dang, Yuliang Liang, Qiang Liu, Guibing Guo, Jianzhe Zhao, Xingwei Wang

CoRR, 2024

KEBench: A Benchmark on Knowledge Editing for Large Vision-Language Models.

Han Huang, Haitian Zhong, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan

CoRR, 2024

Evolving to the Future: Unseen Event Adaptive Fake News Detection on Social Media.

Jiajun Zhang, Zhixun Li, Qiang Liu, Shu Wu, Liang Wang

CoRR, 2024

Enhancing Temporal Knowledge Graph Forecasting with Large Language Models via Chain-of-History Reasoning.

Yuwei Xia, Ding Wang, Qiang Liu, Liang Wang, Shu Wu, Xiaoyu Zhang

CoRR, 2024

Text-Guided Molecule Generation with Diffusion Language Model.

Haisong Gong, Qiang Liu, Shu Wu, Liang Wang

CoRR, 2024

Can Large Language Models Detect Rumors on Social Media?

Qiang Liu, Xiang Tao, Junfei Wu, Shu Wu, Liang Wang

CoRR, 2024

Semantic Evolvement Enhanced Graph Autoencoder for Rumor Detection.

Xiang Tao, Liang Wang, Qiang Liu, Shu Wu, Liang Wang

Proceedings of the ACM on Web Conference 2024, 2024

CAMLO: Cross-Attentive Multi-View Network for Long-Term Origin-Destination Flow Prediction.

Liang Wang, Hao Fu, Shu Wu, Qiang Liu, Xuelei Tan, Fangsheng Huang, Mengdi Zhang, Wei Wu

Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

Modality-Balanced Learning for Multimedia Recommendation.

Jinghao Zhang, Guofan Liu, Qiang Liu, Shu Wu, Liang Wang

Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization.

Xin Sun, Liang Wang, Qiang Liu, Shu Wu, Zilei Wang, Liang Wang

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

Rethinking Fair Graph Neural Networks from Re-balancing.

Zhixun Li, Yushun Dong, Qiang Liu, Jeffrey Xu Yu

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

Semantics Fusion of Hierarchical Transformers for Multimodal Named Entity Recognition.

Zhao Tong, Qiang Liu, Haichao Shi, Yuwei Xia, Shu Wu, Xiaoyu Zhang

Proceedings of the Advanced Intelligent Computing Technology and Applications, 2024

Interpretable Multimodal Out-of-Context Detection with Soft Logic Regularization.

Huanhuan Ma, Jinghao Zhang, Qiang Liu, Shu Wu, Liang Wang

Proceedings of the IEEE International Conference on Acoustics, 2024

Knowledge Graph Enhanced Large Language Model Editing.

Mengqi Zhang, Xiaotian Ye, Qiang Liu, Pengjie Ren, Shu Wu, Zhumin Chen

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Evolving to the Future: Unseen Event Adaptive Fake News Detection on Social Media.

Jiajun Zhang, Zhixun Li, Qiang Liu, Shu Wu, Zilei Wang, Liang Wang

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

CMG: A Causality-enhanced Multi-view Graph Model for Stock Trend Prediction.

Xi Cheng, Liang Wang, Yunan Zeng, Qiang Liu

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Stealthy Attack on Large Language Model based Recommendation.

Jinghao Zhang, Yuting Liu, Qiang Liu, Shu Wu, Guibing Guo, Liang Wang

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

Chain-of-History Reasoning for Temporal Knowledge Graph Forecasting.

Yuwei Xia, Ding Wang, Qiang Liu, Liang Wang, Shu Wu, Xiao-Yu Zhang

Proceedings of the Findings of the Association for Computational Linguistics, 2024

Logical Closed Loop: Uncovering Object Hallucinations in Large Vision-Language Models.

Junfei Wu, Qiang Liu, Ding Wang, Jinghao Zhang, Shu Wu, Liang Wang, Tieniu Tan

Proceedings of the Findings of the Association for Computational Linguistics, 2024

EX-FEVER: A Dataset for Multi-hop Explainable Fact Verification.

Huanhuan Ma, Weizhi Xu, Yifan Wei, Liuji Chen, Liang Wang, Qiang Liu, Shu Wu

Proceedings of the Findings of the Association for Computational Linguistics, 2024

Text-Guided Molecule Generation with Diffusion Language Model.

Haisong Gong, Qiang Liu, Shu Wu, Liang Wang

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

Heterogeneous Graph Reasoning for Fact Checking over Texts and Tables.

Haisong Gong, Weizhi Xu, Shu Wu, Qiang Liu, Liang Wang

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

Rethinking Graph Masked Autoencoders through Alignment and Uniformity.

Liang Wang, Xiang Tao, Qiang Liu, Shu Wu, Liang Wang

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

2023

FedBrain: A robust multi-site brain network analysis framework based on federated learning for brain disease diagnosis.

Chang Zhang, Xiangzhu Meng, Qiang Liu, Shu Wu, Liang Wang, Huansheng Ning

Neurocomputing, November, 2023

Unsupervised Graph Representation Learning with Cluster-aware Self-training and Refining.

Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu

ACM Trans. Intell. Syst. Technol., October, 2023

Latent Structure Mining With Contrastive Modality Fusion for Multimedia Recommendation.

Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Mengqi Zhang, Shu Wu, Liang Wang

IEEE Trans. Knowl. Data Eng., September, 2023

RMT-Net: Reject-Aware Multi-Task Network for Modeling Missing-Not-At-Random Data in Financial Credit Scoring.

Qiang Liu, Yingtao Luo, Shu Wu, Zhen Zhang, Xiangnan Yue, Hong Jin, Liang Wang

IEEE Trans. Knowl. Data Eng., July, 2023

Dynamic Graph Neural Networks for Sequential Recommendation.

Mengqi Zhang, Shu Wu, Xueli Yu, Qiang Liu, Liang Wang

IEEE Trans. Knowl. Data Eng., May, 2023

ID Embedding as Subtle Features of Content and Structure for Multimodal Recommendation.

Yuting Liu, Enneng Yang, Yizhou Dang, Guibing Guo, Qiang Liu, Yuliang Liang, Linying Jiang, Xingwei Wang

CoRR, 2023

EX-FEVER: A Dataset for Multi-hop Explainable Fact Verification.

Huanhuan Ma, Weizhi Xu, Yifan Wei, Liuji Chen, Liang Wang, Qiang Liu, Shu Wu, Liang Wang

CoRR, 2023

GSLB: The Graph Structure Learning Benchmark.

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

CoRR, 2023

Uncovering Neural Scaling Laws in Molecular Representation Learning.

Dingshuo Chen, Yanqiao Zhu, Jieyu Zhang, Yuanqi Du, Zhixun Li, Qiang Liu, Shu Wu, Liang Wang

CoRR, 2023

TCGF: A unified tensorized consensus graph framework for multi-view representation learning.

Xiangzhu Meng, Wei Wei, Qiang Liu, Shu Wu, Liang Wang

CoRR, 2023

TiBGL: Template-induced Brain Graph Learning for Functional Neuroimaging Analysis.

Xiangzhu Meng, Wei Wei, Qiang Liu, Shu Wu, Liang Wang

CoRR, 2023

Deep Stable Multi-Interest Learning for Out-of-distribution Sequential Recommendation.

Qiang Liu, Zhaocheng Liu, Zhenxi Zhu, Shu Wu, Liang Wang

CoRR, 2023

Uncertainty Calibration for Counterfactual Propensity Estimation in Recommendation.

Wenbo Hu, Xin Sun, Qiang Liu, Shu Wu

CoRR, 2023

MetaTKG: Learning Evolutionary Meta-Knowledge for Temporal Knowledge Graph Reasoning.

Yuwei Xia, Mengqi Zhang, Qiang Liu, Shu Wu, Xiao-Yu Zhang

CoRR, 2023

Learning Long- and Short-term Representations for Temporal Knowledge Graph Reasoning.

Mengqi Zhang, Yuwei Xia, Qiang Liu, Shu Wu, Liang Wang

Proceedings of the ACM Web Conference 2023, 2023

Mining Stable Preferences: Adaptive Modality Decorrelation for Multimedia Recommendation.

Jinghao Zhang, Qiang Liu, Shu Wu, Liang Wang

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

GSLB: The Graph Structure Learning Benchmark.

Zhixun Li, Xin Sun, Yifan Luo, Yanqiao Zhu, Dingshuo Chen, Yingtao Luo, Xiangxin Zhou, Qiang Liu, Shu Wu, Liang Wang, Jeffrey Xu Yu

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

Uncovering Neural Scaling Laws in Molecular Representation Learning.

Dingshuo Chen, Yanqiao Zhu, Jieyu Zhang, Yuanqi Du, Zhixun Li, Qiang Liu, Shu Wu, Liang Wang

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

Physics-Guided Discovery of Highly Nonlinear Parametric Partial Differential Equations.

Yingtao Luo, Qiang Liu, Yuntian Chen, Wenbo Hu, Tian Tian, Jun Zhu

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design.

Jiaqi Guan, Xiangxin Zhou, Yuwei Yang, Yu Bao, Jian Peng, Jianzhu Ma, Qiang Liu, Liang Wang, Quanquan Gu

Proceedings of the International Conference on Machine Learning, 2023

Noise-Robust Semi-Supervised Learning for Distantly Supervised Relation Extraction.

Xin Sun, Qiang Liu, Shu Wu, Zilei Wang, Liang Wang

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Personalized Interest Sustainability Modeling for Sequential POI Recommendation.

Zewen Long, Liang Wang, Qiang Liu, Shu Wu

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

Learning Latent Relations for Temporal Knowledge Graph Reasoning.

Mengqi Zhang, Yuwei Xia, Qiang Liu, Shu Wu, Liang Wang

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Counterfactual Debiasing for Fact Verification.

Weizhi Xu, Qiang Liu, Shu Wu, Liang Wang

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

Improving Molecular Pretraining with Complementary Featurizations.

Yanqiao Zhu, Dingshuo Chen, Yuanqi Du, Yingze Wang, Qiang Liu, Shu Wu

CoRR, 2022

Improving Multi-Interest Network with Stable Learning.

Zhaocheng Liu, Yingtao Luo, Di Zeng, Qiang Liu, Daqing Chang, Dongying Kong, Zhi Chen

CoRR, 2022

LPFS: Learnable Polarizing Feature Selection for Click-Through Rate Prediction.

Yi Guo, Zhaocheng Liu, Jianchao Tan, Chao Liao, Daqing Chang, Qiang Liu, Sen Yang, Ji Liu, Dongying Kong, Zhi Chen, Chengru Song

CoRR, 2022

Mining Fine-grained Semantics via Graph Neural Networks for Evidence-based Fake News Detection.

Weizhi Xu, Junfei Wu, Qiang Liu, Shu Wu, Liang Wang

CoRR, 2022

Evidence-aware Fake News Detection with Graph Neural Networks.

Weizhi Xu, Junfei Wu, Qiang Liu, Shu Wu, Liang Wang

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Bias Mitigation for Evidence-aware Fake News Detection by Causal Intervention.

Junfei Wu, Qiang Liu, Weizhi Xu, Shu Wu

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

Structure-Enhanced Heterogeneous Graph Contrastive Learning.

Yanqiao Zhu, Yichen Xu, Hejie Cui, Carl Yang, Qiang Liu, Shu Wu

Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

Bi-directional Contrastive Distillation for Multi-behavior Recommendation.

Yabo Chu, Enneng Yang, Qiang Liu, Yuting Liu, Linying Jiang, Guibing Guo

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

A Survey on Deep Graph Generation: Methods and Applications.

Yanqiao Zhu, Yuanqi Du, Yinkai Wang, Yichen Xu, Jieyu Zhang, Qiang Liu, Shu Wu

Proceedings of the Learning on Graphs Conference, 2022

GraphDIVE: Graph Classification by Mixture of Diverse Experts.

Fenyu Hu, Liping Wang, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Deep Stable Representation Learning on Electronic Health Records.

Yingtao Luo, Zhaocheng Liu, Qiang Liu

Proceedings of the IEEE International Conference on Data Mining, 2022

The Devil is in the Conflict: Disentangled Information Graph Neural Networks for Fraud Detection.

Zhixun Li, Dingshuo Chen, Qiang Liu, Shu Wu

Proceedings of the IEEE International Conference on Data Mining, 2022

MetaTKG: Learning Evolutionary Meta-Knowledge for Temporal Knowledge Graph Reasoning.

Yuwei Xia, Mengqi Zhang, Qiang Liu, Shu Wu, Xiaoyu Zhang

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Multi-Cause Learning for Diagnosis Prediction.

Liping Wang, Qiang Liu, Huanhuan Ma, Shu Wu, Liang Wang

Proceedings of the Data Mining and Big Data - 7th International Conference, 2022

Deep Contrastive Multiview Network Embedding.

Mengqi Zhang, Yanqiao Zhu, Qiang Liu, Shu Wu, Liang Wang

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Second-Order Global Attention Networks for Graph Classification and Regression.

Fenyu Hu, Zeyu Cui, Shu Wu, Qiang Liu, Jinlin Wu, Liang Wang, Tieniu Tan

Proceedings of the Artificial Intelligence - Second CAAI International Conference, 2022

Uncertainty Estimation Based Doubly Robust Learning for Debiasing Recommendation.

Chenyang Su, Qiang Liu, Liang Wang

Proceedings of the 8th IEEE International Conference on Cloud Computing and Intelligent Systems, 2022

2021

Disentangled Item Representation for Recommender Systems.

Zeyu Cui, Feng Yu, Shu Wu, Qiang Liu, Liang Wang

ACM Trans. Intell. Syst. Technol., 2021

Latent Structures Mining with Contrastive Modality Fusion for Multimedia Recommendation.

Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Mengqi Zhang, Shu Wu, Liang Wang

CoRR, 2021

Structure-Aware Hard Negative Mining for Heterogeneous Graph Contrastive Learning.

Yanqiao Zhu, Yichen Xu, Hejie Cui, Carl Yang, Qiang Liu, Shu Wu

CoRR, 2021

Any equation is a forest: Symbolic genetic algorithm for discovering open-form partial differential equations (SGA-PDE).

Yuntian Chen, Yingtao Luo, Qiang Liu, Hao Xu, Dongxiao Zhang

CoRR, 2021

KO-PDE: Kernel Optimized Discovery of Partial Differential Equations with Varying Coefficients.

Yingtao Luo, Qiang Liu, Yuntian Chen, Wenbo Hu, Jun Zhu

CoRR, 2021

DyGCN: Dynamic Graph Embedding with Graph Convolutional Network.

Zeyu Cui, Zekun Li, Shu Wu, Xiaoyu Zhang, Qiang Liu, Liang Wang, Mengmeng Ai

CoRR, 2021

Deep Graph Structure Learning for Robust Representations: A Survey.

Yanqiao Zhu, Weizhi Xu, Jinghao Zhang, Qiang Liu, Shu Wu, Liang Wang

CoRR, 2021

DNN2LR: Automatic Feature Crossing for Credit Scoring.

Qiang Liu, Zhaocheng Liu, Haoli Zhang, Yuntian Chen, Jun Zhu

CoRR, 2021

Disentangled Self-Attentive Neural Networks for Click-Through Rate Prediction.

Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang

CoRR, 2021

STAN: Spatio-Temporal Attention Network for Next Location Recommendation.

Yingtao Luo, Qiang Liu, Zhaocheng Liu

Proceedings of the WWW '21: The Web Conference 2021, 2021

Graph Contrastive Learning with Adaptive Augmentation.

Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang

Proceedings of the WWW '21: The Web Conference 2021, 2021

An Empirical Study of Graph Contrastive Learning.

Yanqiao Zhu, Yichen Xu, Qiang Liu, Shu Wu

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Mining Latent Structures for Multimedia Recommendation.

Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Shu Wu, Shuhui Wang, Liang Wang

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

Relation-aware Heterogeneous Graph for User Profiling.

Qilong Yan, Yufeng Zhang, Qiang Liu, Shu Wu, Liang Wang

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Disentangled Self-Attentive Neural Networks for Click-Through Rate Prediction.

Yichen Xu, Yanqiao Zhu, Feng Yu, Qiang Liu, Shu Wu

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Mining Cross Features for Financial Credit Risk Assessment.

Qiang Liu, Zhaocheng Liu, Haoli Zhang, Yuntian Chen, Jun Zhu

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Deep Active Learning for Text Classification with Diverse Interpretations.

Qiang Liu, Yanqiao Zhu, Zhaocheng Liu, Yufeng Zhang, Shu Wu

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Simplifying Graph Convolutional Networks as Matrix Factorization.

Qiang Liu, Haoli Zhang, Zhaocheng Liu

Proceedings of the Web and Big Data - 5th International Joint Conference, 2021

2020

MV-RNN: A Multi-View Recurrent Neural Network for Sequential Recommendation.

Qiang Cui, Shu Wu, Qiang Liu, Wen Zhong, Liang Wang

IEEE Trans. Knowl. Data Eng., 2020

Deep Active Graph Representation Learning.

Yanqiao Zhu, Weizhi Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang

CoRR, 2020

DNN2LR: Interpretation-inspired Feature Crossing for Real-world Tabular Data.

Zhaocheng Liu, Qiang Liu, Haoli Zhang, Yuntian Chen

CoRR, 2020

Deep Active Learning by Model Interpretability.

Qiang Liu, Zhaocheng Liu, Xiaofang Zhu, Yeliang Xiu, Jun Zhu

CoRR, 2020

Simplification of Graph Convolutional Networks: A Matrix Factorization-based Perspective.

Qiang Liu, Haoli Zhang, Zhaocheng Liu

CoRR, 2020

Deep Graph Contrastive Representation Learning.

Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang

CoRR, 2020

An Empirical Study on Feature Discretization.

Qiang Liu, Zhaocheng Liu, Haoli Zhang

CoRR, 2020

TAGNN: Target Attentive Graph Neural Networks for Session-based Recommendation.

Feng Yu, Yanqiao Zhu, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

TFNet: Multi-Semantic Feature Interaction for CTR Prediction.

Shu Wu, Feng Yu, Xueli Yu, Qiang Liu, Liang Wang, Tieniu Tan, Jie Shao, Fan Huang

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Deep Interaction Machine: A Simple but Effective Model for High-order Feature Interactions.

Feng Yu, Zhaocheng Liu, Qiang Liu, Haoli Zhang, Shu Wu, Liang Wang

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

2019

Learning Preferences and Demands in Visual Recommendation.

Qiang Liu, Shu Wu, Liang Wang

CoRR, 2019

Attention-based convolutional approach for misinformation identification from massive and noisy microblog posts.

Feng Yu, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan

Comput. Secur., 2019

Towards Accurate and Interpretable Sequential Prediction: A CNN & Attention-Based Feature Extractor.

Jingyi Wang, Qiang Liu, Zhaocheng Liu, Shu Wu

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

2018

Mining Significant Microblogs for Misinformation Identification: An Attention-Based Approach.

Qiang Liu, Feng Yu, Shu Wu, Liang Wang

ACM Trans. Intell. Syst. Technol., 2018

2017

Context-Aware Collaborative Prediction

Shu Wu, Qiang Liu, Liang Wang, Tieniu Tan

Springer Briefs in Computer Science, Springer, ISBN: 978-981-10-5372-6, 2017

Multi-Behavioral Sequential Prediction with Recurrent Log-Bilinear Model.

Qiang Liu, Shu Wu, Liang Wang

IEEE Trans. Knowl. Data Eng., 2017

DeepStyle: Learning User Preferences for Visual Recommendation.

Qiang Liu, Shu Wu, Liang Wang

Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2017

A Convolutional Approach for Misinformation Identification.

Feng Yu, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016

Contextual Operation for Recommender Systems.

Shu Wu, Qiang Liu, Liang Wang, Tieniu Tan

IEEE Trans. Knowl. Data Eng., 2016

ICE: Information Credibility Evaluation on Social Media via Representation Learning.

Qiang Liu, Shu Wu, Feng Yu, Liang Wang, Tieniu Tan

CoRR, 2016

Multi-behavioral Sequential Prediction for Collaborative Filtering.

Qiang Liu, Shu Wu, Liang Wang

CoRR, 2016

A Visual and Textual Recurrent Neural Network for Sequential Prediction.

Qiang Cui, Shu Wu, Qiang Liu, Liang Wang

CoRR, 2016

A Dynamic Recurrent Model for Next Basket Recommendation.

Feng Yu, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan

Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, 2016

Context-Aware Sequential Recommendation.

Qiang Liu, Shu Wu, Diyi Wang, Zhaokang Li, Liang Wang

Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Information Credibility Evaluation on Social Media.

Shu Wu, Qiang Liu, Yong Liu, Liang Wang, Tieniu Tan

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

SAPE: A System for Situation-Aware Public Security Evaluation.

Shu Wu, Qiang Liu, Ping Bai, Liang Wang, Tieniu Tan

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Predicting the Next Location: A Recurrent Model with Spatial and Temporal Contexts.

Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

A Convolutional Click Prediction Model.

Qiang Liu, Feng Yu, Shu Wu, Liang Wang

Proceedings of the 24th ACM International Conference on Information and Knowledge Management, 2015

Collaborative Prediction for Multi-entity Interaction With Hierarchical Representation.

Qiang Liu, Shu Wu, Liang Wang

Proceedings of the 24th ACM International Conference on Information and Knowledge Management, 2015

COT: Contextual Operating Tensor for Context-Aware Recommender Systems.

Qiang Liu, Shu Wu, Liang Wang

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015