Bingbing Xu

According to our database, Bingbing Xu authored at least 45 papers between 2017 and 2025.

Collaborative distances:

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

2025

KnowCoder-V2: Deep Knowledge Analysis.

Zixuan Li, Wenxuan Liu, Long Bai, Chunmao Zhang, Wei Li, Fenghui Zhang, Quanxin Jin, Ruoyun He, Zhuo Chen, Zhilei Hu, Fei Wang, Bingbing Xu, Xuhui Jiang, Xiaolong Jin, Jiafeng Guo, Xueqi Cheng

CoRR, June, 2025

Inference-time Alignment in Continuous Space.

Yige Yuan, Teng Xiao, Li Yunfan, Bingbing Xu, Shuchang Tao, Yunqi Qiu, Huawei Shen, Xueqi Cheng

CoRR, May, 2025

Incentivizing Strong Reasoning from Weak Supervision.

Yige Yuan, Teng Xiao, Shuchang Tao, Xue Wang, Jinyang Gao, Bolin Ding, Bingbing Xu

CoRR, May, 2025

Domain Adaptation for Graph Representation Learning: Challenges, Progress, and Prospects.

Boshen Shi, Yongqing Wang, Fangda Guo, Bing-Bing Xu, Hua-Wei Shen, Xueqi Cheng

J. Comput. Sci. Technol., March, 2025

MIGE: A Unified Framework for Multimodal Instruction-Based Image Generation and Editing.

Xueyun Tian, Wei Li, Bingbing Xu, Yige Yuan, Yuanzhuo Wang, Huawei Shen

CoRR, February, 2025

Unveiling the Potential of LLMs in Simulated Society: A Knowledge-Driven LLM Agent Framework for User Modeling.

Shengmao Zhu, Bingbing Xu, Yige Yuan, Bin Xie, Yunfan Li, Huawei Shen

Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

Fact-Level Calibration and Correction for Long-Form Generations.

Yige Yuan, Bingbing Xu, Hexiang Tan, Fei Sun, Teng Xiao, Wei Li, Huawei Shen, Xueqi Cheng

Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

InfoNCE is a Free Lunch for Semantically guided Graph Contrastive Learning.

Zixu Wang, Bingbing Xu, Yige Yuan, Huawei Shen, Xueqi Cheng

Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

From Outcomes to Processes: Guiding PRM Learning from ORM for Inference-Time Alignment.

Bin Xie, Bingbing Xu, Yige Yuan, Shengmao Zhu, Huawei Shen

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

Identity-Preserving Adversarial Training for Robust Network Embedding.

Keting Cen, Hua-Wei Shen, Qi Cao, Bing-Bing Xu, Xueqi Cheng

J. Comput. Sci. Technol., March, 2024

Towards generalizable Graph Contrastive Learning: An information theory perspective.

Yige Yuan, Bingbing Xu, Huawei Shen, Qi Cao, Keting Cen, Wen Zheng, Xueqi Cheng

Neural Networks, 2024

IDEA: Invariant defense for graph adversarial robustness.

Shuchang Tao, Qi Cao, Huawei Shen, Yunfan Wu, Bingbing Xu, Xueqi Cheng

Inf. Sci., 2024

Fact-Level Confidence Calibration and Self-Correction.

Yige Yuan, Bingbing Xu, Hexiang Tan, Fei Sun, Teng Xiao, Wei Li, Huawei Shen, Xueqi Cheng

CoRR, 2024

MITA: Bridging the Gap between Model and Data for Test-time Adaptation.

Yige Yuan, Bingbing Xu, Teng Xiao, Liang Hou, Fei Sun, Huawei Shen, Xueqi Cheng

CoRR, 2024

Graph Domain Adaptation: Challenges, Progress and Prospects.

Boshen Shi, Yongqing Wang, Fangda Guo, Bingbing Xu, Huawei Shen, Xueqi Cheng

CoRR, 2024

Negative as Positive: Enhancing Out-of-distribution Generalization for Graph Contrastive Learning.

Zixu Wang, Bingbing Xu, Yige Yuan, Huawei Shen, Xueqi Cheng

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

SACH: Significant-Attributed Community Search in Heterogeneous Information Networks.

Yanghao Liu, Fangda Guo, Bingbing Xu, Peng Bao, Huawei Shen, Xueqi Cheng

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

History Driven Sampling for Scalable Graph Neural Networks.

Yang Li, Bingbing Xu, Fei Sun, Qi Cao, Yige Yuan, Huawei Shen, Xueqi Cheng

Proceedings of the Database Systems for Advanced Applications, 2024

TEA: Test-Time Energy Adaptation.

Yige Yuan, Bingbing Xu, Liang Hou, Fei Sun, Huawei Shen, Xueqi Cheng

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

PDE+: Enhancing Generalization via PDE with Adaptive Distributional Diffusion.

Yige Yuan, Bingbing Xu, Bo Lin, Liang Hou, Fei Sun, Huawei Shen, Xueqi Cheng

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

2023

Significant-attributed Community Search in Heterogeneous Information Networks.

Yanghao Liu, Fangda Guo, Bingbing Xu, Peng Bao, Huawei Shen, Xueqi Cheng

CoRR, 2023

IDEA: Invariant Causal Defense for Graph Adversarial Robustness.

Shuchang Tao, Qi Cao, Huawei Shen, Yunfan Wu, Bingbing Xu, Xueqi Cheng

CoRR, 2023

Towards Deeper Graph Neural Networks via Layer-Adaptive.

Bingbing Xu, Bin Xie, Huawei Shen

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Simple Multi-view Can Bring Powerful Graph Neural Network.

Bingbing Xu, Yang Li, Qi Cao, Huawei Shen

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Predicting the Silent Majority on Graphs: Knowledge Transferable Graph Neural Network.

Wendong Bi, Bingbing Xu, Xiaoqian Sun, Easton Li Xu, Huawei Shen, Xueqi Cheng

Proceedings of the ACM Web Conference 2023, 2023

MIDLG: Mutual Information based Dual Level GNN for Transaction Fraud Complaint Verification.

Wen Zheng, Bingbing Xu, Emiao Lu, Yang Li, Qi Cao, Xuan Zong, Huawei Shen

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

DyTed: Disentangled Representation Learning for Discrete-time Dynamic Graph.

Kaike Zhang, Qi Cao, Gaolin Fang, Bingbing Xu, Hongjian Zou, Huawei Shen, Xueqi Cheng

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

When Spatio-Temporal Meet Wavelets: Disentangled Traffic Forecasting via Efficient Spectral Graph Attention Networks.

Yuchen Fang, Yanjun Qin, Haiyong Luo, Fang Zhao, Bingbing Xu, Liang Zeng, Chenxing Wang

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

DCGNN: Dual-Channel Graph Neural Network for Social Bot Detection.

Nuoyan Lyu, Bingbing Xu, Fangda Guo, Huawei Shen

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

Bridged-GNN: Knowledge Bridge Learning for Effective Knowledge Transfer.

Wendong Bi, Xueqi Cheng, Bingbing Xu, Xiaoqian Sun, Easton Li Xu, Huawei Shen

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

2022

Location-aware convolutional neural networks for graph classification.

Zhaohui Wang, Qi Cao, Huawei Shen, Bingbing Xu, Keting Cen, Xueqi Cheng

Neural Networks, 2022

Hierarchical Estimation for Effective and Efficient Sampling Graph Neural Network.

Yang Li, Bingbing Xu, Qi Cao, Yige Yuan, Huawei Shen

CoRR, 2022

DyTed: Disentangling Temporal Invariance and Fluctuations in Dynamic Graph Representation Learning.

Kaike Zhang, Qi Cao, Gaolin Fang, Bingbing Xu, Hongjian Zou, Huawei Shen, Xueqi Cheng

CoRR, 2022

Twin Weisfeiler-Lehman: High Expressive GNNs for Graph Classification.

Zhaohui Wang, Qi Cao, Huawei Shen, Bingbing Xu, Xueqi Cheng

CoRR, 2022

Towards Efficient and Expressive GNNs for Graph Classification via Subgraph-Aware Weisfeiler-Lehman.

Zhaohui Wang, Qi Cao, Huawei Shen, Bingbing Xu, Muhan Zhang, Xueqi Cheng

Proceedings of the Learning on Graphs Conference, 2022

Company-as-Tribe: Company Financial Risk Assessment on Tribe-Style Graph with Hierarchical Graph Neural Networks.

Wendong Bi, Bingbing Xu, Xiaoqian Sun, Zidong Wang, Huawei Shen, Xueqi Cheng

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Coordinate Mapping Method of Crowdsourced Data for Indoor Fingerprint Localization.

Zhengyi Li, Wen Li, Dongyan Wei, Hong Yuan, Bingbing Xu, Huawei Shen

Proceedings of the 12th IEEE International Conference on Indoor Positioning and Indoor Navigation, 2022

Towards Powerful Graph Contrastive Learning without Negative Examples.

Keting Cen, Huawei Shen, Qi Cao, Bingbing Xu, Xueqi Cheng

Proceedings of the International Joint Conference on Neural Networks, 2022

2021

Towards Consumer Loan Fraud Detection: Graph Neural Networks with Role-Constrained Conditional Random Field.

Bingbing Xu, Huawei Shen, Bing-Jie Sun, Rong An, Qi Cao, Xueqi Cheng

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Label-Consistency based Graph Neural Networks for Semi-supervised Node Classification.

Bingbing Xu, Junjie Huang, Liang Hou, Huawei Shen, Jinhua Gao, Xueqi Cheng

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

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, Qi Cao, Xinyu Yue, Bingbing Xu, Keting Cen, Huawei Shen

Data Intell., 2019

A Graph Auto-Encoder for Attributed Network Embedding.

Keting Cen, Huawei Shen, Jinhua Gao, Qi Cao, Bingbing Xu, Xueqi Cheng

CoRR, 2019

Graph Convolutional Networks using Heat Kernel for Semi-supervised Learning.

Bingbing Xu, Huawei Shen, Qi Cao, Keting Cen, Xueqi Cheng

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Graph Wavelet Neural Network.

Bingbing Xu, Huawei Shen, Qi Cao, Yunqi Qiu, Xueqi Cheng

Proceedings of the 7th International Conference on Learning Representations, 2019

2017

Ict_spring Belief and Sentiment System at TAC 2017.

Yihan Ni, Bingbing Xu, Yue Zhao, Hui Du

Proceedings of the 2017 Text Analysis Conference, 2017