Ict_spring Belief and Sentiment System at TAC 2017. - Yihan Ni; Bingbing Xu 001; Yue Zhao; Hui Du (TAC, 2017)

Graph Wavelet Neural Network. - Bingbing Xu 001; Huawei Shen; Qi Cao; Yunqi Qiu; Xueqi Cheng (ICLR (Poster), 2019)

Graph Convolutional Networks using Heat Kernel for Semi-supervised Learning. - Bingbing Xu 001; Huawei Shen; Qi Cao; Keting Cen; Xueqi Cheng (IJCAI, 2019)

A Graph Auto-Encoder for Attributed Network Embedding. - Keting Cen; Huawei Shen; Jinhua Gao; Qi Cao; Bingbing Xu 001; Xueqi Cheng (CoRR, 2019)

User Profiling for CSDN: Keyphrase Extraction, User Tagging and User Growth Value Prediction: First-place Entry for User Profiling Technology Evaluation Campaign in SMP Cup 2017. - Guoliang Xing; Hao Gao 009; Qi Cao; Xinyu Yue; Bingbing Xu 001; Keting Cen; Huawei Shen (Data Intell., 2019)

Label-Consistency based Graph Neural Networks for Semi-supervised Node Classification. - Bingbing Xu 001; Junjie Huang; Liang Hou; Huawei Shen; Jinhua Gao; Xueqi Cheng (SIGIR, 2020)

Towards Consumer Loan Fraud Detection: Graph Neural Networks with Role-Constrained Conditional Random Field. - Bingbing Xu 001; Huawei Shen; Bing-Jie Sun; Rong An; Qi Cao; Xueqi Cheng (AAAI, 2021)

Towards Powerful Graph Contrastive Learning without Negative Examples. - Keting Cen; Huawei Shen; Qi Cao; Bingbing Xu 001; Xueqi Cheng (IJCNN, 2022)

Coordinate Mapping Method of Crowdsourced Data for Indoor Fingerprint Localization. - Zhengyi Li; Wen Li; Dongyan Wei; Hong Yuan; Bingbing Xu 001; Huawei Shen (IPIN, 2022)

Company-as-Tribe: Company Financial Risk Assessment on Tribe-Style Graph with Hierarchical Graph Neural Networks. - Wendong Bi; Bingbing Xu 001; Xiaoqian Sun; Zidong Wang 007; Huawei Shen; Xueqi Cheng (KDD, 2022)

Towards Efficient and Expressive GNNs for Graph Classification via Subgraph-Aware Weisfeiler-Lehman. - Zhaohui Wang; Qi Cao; Huawei Shen; Bingbing Xu 001; Muhan Zhang; Xueqi Cheng (LoG, 2022)

Twin Weisfeiler-Lehman: High Expressive GNNs for Graph Classification. - Zhaohui Wang; Qi Cao; Huawei Shen; Bingbing Xu 001; Xueqi Cheng (CoRR, 2022)

DyTed: Disentangling Temporal Invariance and Fluctuations in Dynamic Graph Representation Learning. - Kaike Zhang; Qi Cao; Gaolin Fang; Bingbing Xu 001; Hongjian Zou; Huawei Shen; Xueqi Cheng (CoRR, 2022)

Hierarchical Estimation for Effective and Efficient Sampling Graph Neural Network. - Yang Li 202; Bingbing Xu 001; Qi Cao; Yige Yuan; Huawei Shen (CoRR, 2022)

Location-aware convolutional neural networks for graph classification. - Zhaohui Wang; Qi Cao; Huawei Shen; Bingbing Xu 001; Keting Cen; Xueqi Cheng (Neural Networks, 2022)

Bridged-GNN: Knowledge Bridge Learning for Effective Knowledge Transfer. - Wendong Bi; Xueqi Cheng; Bingbing Xu 001; Xiaoqian Sun; Easton Li Xu; Huawei Shen (CIKM, 2023)

DCGNN: Dual-Channel Graph Neural Network for Social Bot Detection. - Nuoyan Lyu; Bingbing Xu 001; Fangda Guo; Huawei Shen (CIKM, 2023)

When Spatio-Temporal Meet Wavelets: Disentangled Traffic Forecasting via Efficient Spectral Graph Attention Networks. - Yuchen Fang 001; Yanjun Qin; Haiyong Luo; Fang Zhao 003; Bingbing Xu 001; Liang Zeng 002; Chenxing Wang 001 (ICDE, 2023)

DyTed: Disentangled Representation Learning for Discrete-time Dynamic Graph. - Kaike Zhang; Qi Cao; Gaolin Fang; Bingbing Xu 001; Hongjian Zou; Huawei Shen; Xueqi Cheng (KDD, 2023)

MIDLG: Mutual Information based Dual Level GNN for Transaction Fraud Complaint Verification. - Wen Zheng; Bingbing Xu 001; Emiao Lu; Yang Li 202; Qi Cao; Xuan Zong 001; Huawei Shen (KDD, 2023)

Predicting the Silent Majority on Graphs: Knowledge Transferable Graph Neural Network. - Wendong Bi; Bingbing Xu 001; Xiaoqian Sun; Easton Li Xu; Huawei Shen; Xueqi Cheng (WWW, 2023)

Simple Multi-view Can Bring Powerful Graph Neural Network. - Bingbing Xu 001; Yang Li 202; Qi Cao; Huawei Shen (WWW (Companion Volume), 2023)

Towards Deeper Graph Neural Networks via Layer-Adaptive. - Bingbing Xu 001; Bin Xie; Huawei Shen (WWW (Companion Volume), 2023)

IDEA: Invariant Causal Defense for Graph Adversarial Robustness. - Shuchang Tao; Qi Cao; Huawei Shen; Yunfan Wu; Bingbing Xu 001; Xueqi Cheng (CoRR, 2023)

Significant-attributed Community Search in Heterogeneous Information Networks. - Yanghao Liu; Fangda Guo; Bingbing Xu 001; Peng Bao; Huawei Shen; Xueqi Cheng (CoRR, 2023)

PDE+: Enhancing Generalization via PDE with Adaptive Distributional Diffusion. - Yige Yuan; Bingbing Xu 001; Bo Lin; Liang Hou; Fei Sun 001; Huawei Shen; Xueqi Cheng (AAAI, 2024)

TEA: Test-Time Energy Adaptation. - Yige Yuan; Bingbing Xu 001; Liang Hou; Fei Sun 001; Huawei Shen; Xueqi Cheng (CVPR, 2024)

History Driven Sampling for Scalable Graph Neural Networks. - Yang Li 202; Bingbing Xu 001; Fei Sun 001; Qi Cao; Yige Yuan; Huawei Shen; Xueqi Cheng (DASFAA (6), 2024)

SACH: Significant-Attributed Community Search in Heterogeneous Information Networks. - Yanghao Liu; Fangda Guo; Bingbing Xu 001; Peng Bao; Huawei Shen; Xueqi Cheng (ICDE, 2024)

Negative as Positive: Enhancing Out-of-distribution Generalization for Graph Contrastive Learning. - Zixu Wang; Bingbing Xu 001; Yige Yuan; Huawei Shen; Xueqi Cheng (SIGIR, 2024)

Graph Domain Adaptation: Challenges, Progress and Prospects. - Boshen Shi; Yongqing Wang 005; Fangda Guo; Bingbing Xu 001; Huawei Shen; Xueqi Cheng (CoRR, 2024)

MITA: Bridging the Gap between Model and Data for Test-time Adaptation. - Yige Yuan; Bingbing Xu 001; Teng Xiao; Liang Hou; Fei Sun 001; Huawei Shen; Xueqi Cheng (CoRR, 2024)

Fact-Level Confidence Calibration and Self-Correction. - Yige Yuan; Bingbing Xu 001; Hexiang Tan; Fei Sun 001; Teng Xiao; Wei Li 176; Huawei Shen; Xueqi Cheng (CoRR, 2024)

IDEA: Invariant defense for graph adversarial robustness. - Shuchang Tao; Qi Cao; Huawei Shen; Yunfan Wu; Bingbing Xu 001; Xueqi Cheng (Inf. Sci., 2024)

Towards generalizable Graph Contrastive Learning: An information theory perspective. - Yige Yuan; Bingbing Xu 001; Huawei Shen; Qi Cao; Keting Cen; Wen Zheng; Xueqi Cheng (Neural Networks, 2024)

Identity-Preserving Adversarial Training for Robust Network Embedding. - Keting Cen; Hua-Wei Shen; Qi Cao; Bing-Bing Xu 001; Xueqi Cheng (J. Comput. Sci. Technol., 2024)

From Outcomes to Processes: Guiding PRM Learning from ORM for Inference-Time Alignment. - Bin Xie; Bingbing Xu 001; Yige Yuan; Shengmao Zhu; Huawei Shen (ACL (1), 2025)

InfoNCE is a Free Lunch for Semantically guided Graph Contrastive Learning. - Zixu Wang; Bingbing Xu 001; Yige Yuan; Huawei Shen; Xueqi Cheng (SIGIR, 2025)

Fact-Level Calibration and Correction for Long-Form Generations. - Yige Yuan; Bingbing Xu 001; Hexiang Tan; Fei Sun 001; Teng Xiao; Wei Li 176; Huawei Shen; Xueqi Cheng (SIGIR, 2025)

Unveiling the Potential of LLMs in Simulated Society: A Knowledge-Driven LLM Agent Framework for User Modeling. - Shengmao Zhu; Bingbing Xu 001; Yige Yuan; Bin Xie; Yunfan Li; Huawei Shen (WWW (Companion Volume), 2025)

MIGE: A Unified Framework for Multimodal Instruction-Based Image Generation and Editing. - Xueyun Tian; Wei Li 176; Bingbing Xu 001; Yige Yuan; Yuanzhuo Wang; Huawei Shen (CoRR, 2025)

Domain Adaptation for Graph Representation Learning: Challenges, Progress, and Prospects. - Boshen Shi; Yongqing Wang 005; Fangda Guo; Bing-Bing Xu 001; Hua-Wei Shen; Xueqi Cheng (J. Comput. Sci. Technol., 2025)

Incentivizing Strong Reasoning from Weak Supervision. - Yige Yuan; Teng Xiao; Shuchang Tao; Xue Wang 010; Jinyang Gao; Bolin Ding; Bingbing Xu 001 (CoRR, 2025)

Inference-time Alignment in Continuous Space. - Yige Yuan; Teng Xiao; Li Yunfan; Bingbing Xu 001; Shuchang Tao; Yunqi Qiu; Huawei Shen; Xueqi Cheng (CoRR, 2025)

KnowCoder-V2: Deep Knowledge Analysis. - Zixuan Li 001; Wenxuan Liu; Long Bai 002; Chunmao Zhang; Wei Li 176; Fenghui Zhang; Quanxin Jin; Ruoyun He; Zhuo Chen; Zhilei Hu; Fei Wang 014; Bingbing Xu 001; et al. (CoRR, 2025)