Wentao Zhang

Orcid: 0000-0002-7532-5550

Affiliations:

Peking University, Beijing, China
Mila - Québec AI Institute, HEC Montréal, Canada (former)

According to our database¹, Wentao Zhang authored at least 119 papers between 2020 and 2025.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

2020

2021

2022

2023

2024

2025

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2025

A Comprehensive Survey on Imbalanced Data Learning.

[BibT_eX]

[DOI]

CoRR, February, 2025

Any2AnyTryon: Leveraging Adaptive Position Embeddings for Versatile Virtual Clothing Tasks.

[BibT_eX]

[DOI]

CoRR, January, 2025

Baichuan-Omni-1.5 Technical Report.

[BibT_eX]

[DOI]

CoRR, January, 2025

Med-R<sup>2</sup>: Crafting Trustworthy LLM Physicians through Retrieval and Reasoning of Evidence-Based Medicine.

[BibT_eX]

[DOI]

CoRR, January, 2025

2024

Graphusion: Latent Diffusion for Graph Generation.

[BibT_eX]

[DOI]

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

Distributed Graph Neural Network Training: A Survey.

[BibT_eX]

[DOI]

ACM Comput. Surv., August, 2024

OUTRE: An OUT-of-core De-REdundancy GNN Training Framework for Massive Graphs within A Single Machine.

[BibT_eX]

[DOI]

Proc. VLDB Endow., July, 2024

Diffusion Models: A Comprehensive Survey of Methods and Applications.

[BibT_eX]

[DOI]

ACM Comput. Surv., April, 2024

LightDiC: A Simple yet Effective Approach for Large-scale Digraph Representation Learning.

[BibT_eX]

[DOI]

Proc. VLDB Endow., March, 2024

Individual and Structural Graph Information Bottlenecks for Out-of-Distribution Generalization.

[BibT_eX]

[DOI]

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

OpenBox: A Python Toolkit for Generalized Black-box Optimization.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2024

FedVCK: Non-IID Robust and Communication-Efficient Federated Learning via Valuable Condensed Knowledge for Medical Image Analysis.

[BibT_eX]

[DOI]

CoRR, 2024

Training-free Heterogeneous Graph Condensation via Data Selection.

[BibT_eX]

[DOI]

CoRR, 2024

Towards Scalable and Deep Graph Neural Networks via Noise Masking.

[BibT_eX]

[DOI]

CoRR, 2024

Memory-enhanced Invariant Prompt Learning for Urban Flow Prediction under Distribution Shifts.

[BibT_eX]

[DOI]

Haiyang Jiang

Tong Chen

Wentao Zhang

Nguyen Quoc Viet Hung

Yuan Yuan

Yong Li

Lizhen Cui

CoRR, 2024

Contrastive Graph Condensation: Advancing Data Versatility through Self-Supervised Learning.

[BibT_eX]

[DOI]

CoRR, 2024

Epidemiology-informed Network for Robust Rumor Detection.

[BibT_eX]

[DOI]

CoRR, 2024

VersaTune: An Efficient Data Composition Framework for Training Multi-Capability LLMs.

[BibT_eX]

[DOI]

CoRR, 2024

SiriusBI: Building End-to-End Business Intelligence Enhanced by Large Language Models.

[BibT_eX]

[DOI]

CoRR, 2024

Baichuan Alignment Technical Report.

[BibT_eX]

[DOI]

CoRR, 2024

Facilitating Multi-turn Function Calling for LLMs via Compositional Instruction Tuning.

[BibT_eX]

[DOI]

CoRR, 2024

FB-Bench: A Fine-Grained Multi-Task Benchmark for Evaluating LLMs' Responsiveness to Human Feedback.

[BibT_eX]

[DOI]

CoRR, 2024

Multi-Agent Collaborative Data Selection for Efficient LLM Pretraining.

[BibT_eX]

[DOI]

CoRR, 2024

Trans4D: Realistic Geometry-Aware Transition for Compositional Text-to-4D Synthesis.

[BibT_eX]

[DOI]

CoRR, 2024

Gradual Learning: Optimizing Fine-Tuning with Partially Mastered Knowledge in Large Language Models.

[BibT_eX]

[DOI]

CoRR, 2024

Data Proportion Detection for Optimized Data Management for Large Language Models.

[BibT_eX]

[DOI]

CoRR, 2024

Retrofitting Temporal Graph Neural Networks with Transformer.

[BibT_eX]

[DOI]

CoRR, 2024

DataSculpt: Crafting Data Landscapes for LLM Post-Training through Multi-objective Partitioning.

[BibT_eX]

[DOI]

CoRR, 2024

OpenFGL: A Comprehensive Benchmarks for Federated Graph Learning.

[BibT_eX]

[DOI]

CoRR, 2024

BaichuanSEED: Sharing the Potential of ExtensivE Data Collection and Deduplication by Introducing a Competitive Large Language Model Baseline.

[BibT_eX]

[DOI]

CoRR, 2024

SysBench: Can Large Language Models Follow System Messages?

[BibT_eX]

[DOI]

CoRR, 2024

MathScape: Evaluating MLLMs in multimodal Math Scenarios through a Hierarchical Benchmark.

[BibT_eX]

[DOI]

CoRR, 2024

CFBench: A Comprehensive Constraints-Following Benchmark for LLMs.

[BibT_eX]

[DOI]

CoRR, 2024

SynthVLM: High-Efficiency and High-Quality Synthetic Data for Vision Language Models.

[BibT_eX]

[DOI]

CoRR, 2024

PAS: Data-Efficient Plug-and-Play Prompt Augmentation System.

[BibT_eX]

[DOI]

CoRR, 2024

KeyVideoLLM: Towards Large-scale Video Keyframe Selection.

[BibT_eX]

[DOI]

CoRR, 2024

Consistency Flow Matching: Defining Straight Flows with Velocity Consistency.

[BibT_eX]

[DOI]

CoRR, 2024

Efficient-Empathy: Towards Efficient and Effective Selection of Empathy Data.

[BibT_eX]

[DOI]

CoRR, 2024

RobGC: Towards Robust Graph Condensation.

[BibT_eX]

[DOI]

CoRR, 2024

A Survey of Multimodal Large Language Model from A Data-centric Perspective.

[BibT_eX]

[DOI]

CoRR, 2024

EditWorld: Simulating World Dynamics for Instruction-Following Image Editing.

[BibT_eX]

[DOI]

CoRR, 2024

Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class Partition.

[BibT_eX]

[DOI]

Quoc Viet Hung Nguyen

Hongzhi Yin

CoRR, 2024

Acceleration Algorithms in GNNs: A Survey.

[BibT_eX]

[DOI]

CoRR, 2024

Spatial-temporal Memories Enhanced Graph Autoencoder for Anomaly Detection in Dynamic Graphs.

[BibT_eX]

[DOI]

CoRR, 2024

Retrieval-Augmented Generation for AI-Generated Content: A Survey.

[BibT_eX]

[DOI]

CoRR, 2024

Graph Condensation: A Survey.

[BibT_eX]

[DOI]

CoRR, 2024

Rethinking Node-wise Propagation for Large-scale Graph Learning.

[BibT_eX]

[DOI]

Proceedings of the ACM on Web Conference 2024, 2024

NPA: Improving Large-scale Graph Neural Networks with Non-parametric Attention.

[BibT_eX]

[DOI]

Proceedings of the Companion of the 2024 International Conference on Management of Data, 2024

MMGCL: Meta Knowledge-Enhanced Multi-view Graph Contrastive Learning for Recommendations.

[BibT_eX]

[DOI]

Proceedings of the 18th ACM Conference on Recommender Systems, 2024

Distribution-Aware Data Expansion with Diffusion Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Efficient Multi-task LLM Quantization and Serving for Multiple LoRA Adapters.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Graph Condensation for Open-World Graph Learning.

[BibT_eX]

[DOI]

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

Interaction-based Retrieval-augmented Diffusion Models for Protein-specific 3D Molecule Generation.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Protein-Ligand Interaction Prior for Binding-aware 3D Molecule Diffusion Models.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

NC-ALG: Graph-Based Active Learning Under Noisy Crowd.

[BibT_eX]

[DOI]

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

BIM: Improving Graph Neural Networks with Balanced Influence Maximization.

[BibT_eX]

[DOI]

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

Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning.

[BibT_eX]

[DOI]

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

Multi- View Teacher with Curriculum Data Fusion for Robust Unsupervised Domain Adaptation.

[BibT_eX]

[DOI]

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

HGAMLP: Heterogeneous Graph Attention MLP with De-Redundancy Mechanism.

[BibT_eX]

[DOI]

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

AdaFGL: A New Paradigm for Federated Node Classification with Topology Heterogeneity.

[BibT_eX]

[DOI]

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

Accelerating Scalable Graph Neural Network Inference with Node-Adaptive Propagation.

[BibT_eX]

[DOI]

Quoc Viet Hung Nguyen

Bin Cui

Hongzhi Yin

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

Graph Condensation for Inductive Node Representation Learning.

[BibT_eX]

[DOI]

Quoc Viet Hung Nguyen

Kai Zheng

Hongzhi Yin

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

Physics-guided Active Sample Reweighting for Urban Flow Prediction.

[BibT_eX]

[DOI]

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

MetaGXplore: Integrating Multi-Omics Data with Graph Convolutional Networks for Pan-cancer Patient Metastasis Identification.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024

Towards Effective and General Graph Unlearning via Mutual Evolution.

[BibT_eX]

[DOI]

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

2023

P<sup>2</sup>CG: a privacy preserving collaborative graph neural network training framework.

[BibT_eX]

[DOI]

VLDB J., July, 2023

VolcanoML: speeding up end-to-end AutoML via scalable search space decomposition.

[BibT_eX]

[DOI]

VLDB J., March, 2023

Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-Aware Deep Architecture.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2023

FedGTA: Topology-aware Averaging for Federated Graph Learning.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2023

Towards General and Efficient Online Tuning for Spark.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2023

Scapin: Scalable Graph Structure Perturbation by Augmented Influence Maximization.

[BibT_eX]

[DOI]

Proc. ACM Manag. Data, 2023

Graph Neural Networks in Recommender Systems: A Survey.

[BibT_eX]

[DOI]

ACM Comput. Surv., 2023

Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning.

[BibT_eX]

[DOI]

CoRR, 2023

VQGraph: Graph Vector-Quantization for Bridging GNNs and MLPs.

[BibT_eX]

[DOI]

CoRR, 2023

OpenBox: A Python Toolkit for Generalized Black-box Optimization.

[BibT_eX]

[DOI]

CoRR, 2023

Transfer Learning for Bayesian Optimization: A Survey.

[BibT_eX]

[DOI]

CoRR, 2023

Improving Diffusion-Based Image Synthesis with Context Prediction.

[BibT_eX]

[DOI]

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

Rover: An Online Spark SQL Tuning Service via Generalized Transfer Learning.

[BibT_eX]

[DOI]

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

Fairness-aware Maximal Biclique Enumeration on Bipartite Graphs.

[BibT_eX]

[DOI]

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

Semantic-aware Node Synthesis for Imbalanced Heterogeneous Information Networks.

[BibT_eX]

[DOI]

Nguyen Quoc Viet Hung

Hongzhi Yin

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

Graph-Enforced Neural Network for Attributed Graph Clustering.

[BibT_eX]

[DOI]

Proceedings of the Web and Big Data - 7th International Joint Conference, 2023

ProxyBO: Accelerating Neural Architecture Search via Bayesian Optimization with Zero-Cost Proxies.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2022

Diffusion-Based Scene Graph to Image Generation with Masked Contrastive Pre-Training.

[BibT_eX]

[DOI]

CoRR, 2022

Efficient Graph Neural Network Inference at Large Scale.

[BibT_eX]

[DOI]

Xinyi Gao

Wentao Zhang

Yingxia Shao

Quoc Viet Hung Nguyen

Bin Cui

Hongzhi Yin

CoRR, 2022

Diffusion Models: A Comprehensive Survey of Methods and Applications.

[BibT_eX]

[DOI]

CoRR, 2022

Efficient End-to-End AutoML via Scalable Search Space Decomposition.

[BibT_eX]

[DOI]

CoRR, 2022

DFG-NAS: Deep and Flexible Graph Neural Architecture Search.

[BibT_eX]

[DOI]

CoRR, 2022

AutoDC: an automatic machine learning framework for disease classification.

[BibT_eX]

[DOI]

Bioinform., 2022

PaSca: A Graph Neural Architecture Search System under the Scalable Paradigm.

[BibT_eX]

[DOI]

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

K-core decomposition on super large graphs with limited resources.

[BibT_eX]

[DOI]

Proceedings of the SAC '22: The 37th ACM/SIGAPP Symposium on Applied Computing, Virtual Event, April 25, 2022

DivBO: Diversity-aware CASH for Ensemble Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Graph Attention Multi-Layer Perceptron.

[BibT_eX]

[DOI]

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

Model Degradation Hinders Deep Graph Neural Networks.

[BibT_eX]

[DOI]

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

TransBO: Hyperparameter Optimization via Two-Phase Transfer Learning.

[BibT_eX]

[DOI]

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

Transfer Learning based Search Space Design for Hyperparameter Tuning.

[BibT_eX]

[DOI]

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

NAFS: A Simple yet Tough-to-beat Baseline for Graph Representation Learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Deep and Flexible Graph Neural Architecture Search.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Information Gain Propagation: a New Way to Graph Active Learning with Soft Labels.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-aware Deep Architecture (Extended Abstract).

[BibT_eX]

[DOI]

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Zoomer: Boosting Retrieval on Web-scale Graphs by Regions of Interest.

[BibT_eX]

[DOI]

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

2021

Grain: Improving Data Efficiency of Graph Neural Networks via Diversified Influence Maximization.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2021

VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2021

Enhanced review-based rating prediction by exploiting aside information and user influence.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2021

Graph Attention Multi-Layer Perceptron.

[BibT_eX]

[DOI]

CoRR, 2021

Evaluating Deep Graph Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2021

GMLP: Building Scalable and Flexible Graph Neural Networks with Feature-Message Passing.

[BibT_eX]

[DOI]

CoRR, 2021

ALG: Fast and Accurate Active Learning Framework for Graph Convolutional Networks.

[BibT_eX]

[DOI]

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

Node Dependent Local Smoothing for Scalable Graph Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

RIM: Reliable Influence-based Active Learning on Graphs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

ROD: Reception-aware Online Distillation for Sparse Graphs.

[BibT_eX]

[DOI]

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

DeGNN: Improving Graph Neural Networks with Graph Decomposition.

[BibT_eX]

[DOI]

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

OpenBox: A Generalized Black-box Optimization Service.

[BibT_eX]

[DOI]

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020

Graph Neural Networks in Recommender Systems: A Survey.

[BibT_eX]

[DOI]

CoRR, 2020

Snapshot boosting: a fast ensemble framework for deep neural networks.

[BibT_eX]

[DOI]

Sci. China Inf. Sci., 2020

Reliable Data Distillation on Graph Convolutional Network.

[BibT_eX]

[DOI]

Proceedings of the 2020 International Conference on Management of Data, 2020

Efficient Diversity-Driven Ensemble for Deep Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 36th IEEE International Conference on Data Engineering, 2020

Wentao Zhang

Timeline

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