Yonggang Zhang

Orcid: 0000-0002-4080-7592

Affiliations:

Hong Kong Baptist University, Department of Computer Science, Hong Kong

According to our database¹, Yonggang Zhang authored at least 58 papers between 2020 and 2025.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2025

Semantic-guided Fine-tuning of Foundation Model for Long-tailed Visual Recognition.

[BibT_eX]

[DOI]

Yufei Peng

Yonggang Zhang

Yiu-ming Cheung

CoRR, July, 2025

Enhancing Target-unspecific Tasks through a Features Matrix.

[BibT_eX]

[DOI]

CoRR, May, 2025

Out-of-Distribution Detection with Virtual Outlier Smoothing.

[BibT_eX]

[DOI]

Int. J. Comput. Vis., February, 2025

Characterizing Submanifold Region for Out-of-Distribution Detection.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., January, 2025

Shaping pre-trained language models for task-specific embedding generation via consistency calibration.

[BibT_eX]

[DOI]

Raymond Chi-Wing Wong

Yonggang Zhang

Neural Networks, 2025

Consistent prompt learning for vision-language models.

[BibT_eX]

[DOI]

Yonggang Zhang

Xinmei Tian

Knowl. Based Syst., 2025

SENA: Leveraging set-level consistency adversarial learning for robust pre-trained language model adaptation.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2025

InsGNN: Interpretable spatio-temporal graph neural networks via information bottleneck.

[BibT_eX]

[DOI]

Inf. Fusion, 2025

MetaGeno: a chromosome-wise multi-task genomic framework for ischaemic stroke risk prediction.

[BibT_eX]

[DOI]

Briefings Bioinform., 2025

Mitigating Forgetting in Adapting Pre-trained Language Models to Text Processing Tasks via Consistency Alignment.

[BibT_eX]

[DOI]

Proceedings of the ACM on Web Conference 2025, 2025

Distributional Prototype Learning for Out-of-distribution Detection.

[BibT_eX]

[DOI]

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, 2025

Hot-pluggable Federated Learning: Bridging General and Personalized FL via Dynamic Selection.

[BibT_eX]

[DOI]

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Leveraging Submodule Linearity Enhances Task Arithmetic Performance in LLMs.

[BibT_eX]

[DOI]

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detection.

[BibT_eX]

[DOI]

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Characterizing Submanifold Region for Out-of-Distribution Detection: (Extended Abstract).

[BibT_eX]

[DOI]

Proceedings of the 41st IEEE International Conference on Data Engineering, 2025

Tracing and Dissecting How LLMs Recall Factual Knowledge for Real World Questions.

[BibT_eX]

[DOI]

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

Interpret and Improve In-Context Learning via the Lens of Input-Label Mappings.

[BibT_eX]

[DOI]

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

Component-Level Segmentation for Oracle Bone Inscription Decipherment.

[BibT_eX]

[DOI]

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Expert-level diagnosis of pediatric posterior fossa tumors via consistency calibration.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2024

Detecting Discrepancies Between AI-Generated and Natural Images Using Uncertainty.

[BibT_eX]

[DOI]

CoRR, 2024

Rethinking Improved Privacy-Utility Trade-off with Pre-existing Knowledge for DP Training.

[BibT_eX]

[DOI]

CoRR, 2024

Enhancing Multiple Dimensions of Trustworthiness in LLMs via Sparse Activation Control.

[BibT_eX]

[DOI]

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

FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion.

[BibT_eX]

[DOI]

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

Learning to Shape In-distribution Feature Space for Out-of-distribution Detection.

[BibT_eX]

[DOI]

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

Component-Level Oracle Bone Inscription Retrieval.

[BibT_eX]

[DOI]

Proceedings of the 2024 International Conference on Multimedia Retrieval, 2024

Interpreting and Improving Large Language Models in Arithmetic Calculation.

[BibT_eX]

[DOI]

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

From Yes-Men to Truth-Tellers: Addressing Sycophancy in Large Language Models with Pinpoint Tuning.

[BibT_eX]

[DOI]

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

NoiseDiffusion: Correcting Noise for Image Interpolation with Diffusion Models beyond Spherical Linear Interpolation.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Robust Training of Federated Models with Extremely Label Deficiency.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

FedImpro: Measuring and Improving Client Update in Federated Learning.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Out-of-Distribution Detection with Negative Prompts.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Enhancing One-Shot Federated Learning Through Data and Ensemble Co-Boosting.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Federated Learning with Extremely Noisy Clients via Negative Distillation.

[BibT_eX]

[DOI]

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

2023

Invariant Learning via Probability of Sufficient and Necessary Causes.

[BibT_eX]

[DOI]

CoRR, 2023

FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training.

[BibT_eX]

[DOI]

CoRR, 2023

FedFed: Feature Distillation against Data Heterogeneity in Federated Learning.

[BibT_eX]

[DOI]

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

Invariant Learning via Probability of Sufficient and Necessary Causes.

[BibT_eX]

[DOI]

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

SODA: Robust Training of Test-Time Data Adaptors.

[BibT_eX]

[DOI]

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

Learning to Augment Distributions for Out-of-distribution Detection.

[BibT_eX]

[DOI]

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

Moderately Distributional Exploration for Domain Generalization.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Continual Named Entity Recognition without Catastrophic Forgetting.

[BibT_eX]

[DOI]

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Hard Sample Matters a Lot in Zero-Shot Quantization.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Towards Lightweight Black-Box Attacks against Deep Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2022

Pareto Invariant Risk Minimization.

[BibT_eX]

[DOI]

CoRR, 2022

Invariance Principle Meets Out-of-Distribution Generalization on Graphs.

[BibT_eX]

[DOI]

CoRR, 2022

Watermarking for Out-of-distribution Detection.

[BibT_eX]

[DOI]

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

Towards Lightweight Black-Box Attack Against Deep Neural Networks.

[BibT_eX]

[DOI]

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

Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs.

[BibT_eX]

[DOI]

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

Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Adversarial Robustness Through the Lens of Causality.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Understanding and Improving Graph Injection Attack by Promoting Unnoticeability.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Meta Convolutional Neural Networks for Single Domain Generalization.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Prompt Distribution Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Class-Disentanglement and Applications in Adversarial Detection and Defense.

[BibT_eX]

[DOI]

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

2020

Principal Component Adversarial Example.

[BibT_eX]

[DOI]

IEEE Trans. Image Process., 2020

Dual-Path Distillation: A Unified Framework to Improve Black-Box Attacks.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Yonggang Zhang

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