Xiaojin Zhang
Orcid: 0000-0001-9065-6852Affiliations:
- Huazhong University of Science and Technology, Wuhan, China
- Hong Kong University of Science and Technology, Hong Kong (former)
- Chinese University of Hong Kong, Hong Kong (former)
According to our database1,
Xiaojin Zhang authored at least 53 papers
between 2019 and 2026.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
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on orcid.org
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on dl.acm.org
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Bibliography
2026
ViCrop-Det: Spatial Attention Entropy Guided Cropping for Training-Free Small-Object Detection.
CoRR, April, 2026
A Systematic Survey and Benchmark of Deep Learning for Molecular Property Prediction in the Foundation Model Era.
CoRR, April, 2026
CoRR, April, 2026
KVSmooth: Mitigating Hallucination in Multi-modal Large Language Models through Key-Value Smoothing.
CoRR, February, 2026
Perturbation-Induced Linearization: Constructing Unlearnable Data with Solely Linear Classifiers.
CoRR, January, 2026
InsQABench: Benchmarking Chinese insurance domain question answering with large language models.
Inf. Process. Manag., 2026
AutoLink: Autonomous Schema Exploration and Expansion for Scalable Schema Linking in Text-to-SQL at Scale.
Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026
2025
Grounding Foundation Models through Federated Transfer Learning: A General Framework.
ACM Trans. Intell. Syst. Technol., August, 2025
Deciphering the Interplay between Attack and Protection Complexity in Privacy-Preserving Federated Learning.
CoRR, August, 2025
Camouflaged Variational Graph AutoEncoder Against Attribute Inference Attacks for Cross-Domain Recommendation.
IEEE Trans. Knowl. Data Eng., July, 2025
IEEE Trans. Knowl. Data Eng., July, 2025
FedSDAF: Leveraging Source Domain Awareness for Enhanced Federated Domain Generalization.
CoRR, May, 2025
FedEM: A Privacy-Preserving Framework for Concurrent Utility Preservation in Federated Learning.
CoRR, March, 2025
InsQABench: Benchmarking Chinese Insurance Domain Question Answering with Large Language Models.
CoRR, January, 2025
Beyond Right to be Forgotten: Managing Heterogeneity Side Effects Through Strategic Incentives.
Proceedings of the Twenty-sixth International Symposium on Theory, 2025
Proceedings of the 31st International Conference on Computational Linguistics, 2025
FedAA: A Reinforcement Learning Perspective on Adaptive Aggregation for Fair and Robust Federated Learning.
Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025
2024
A Meta-Learning Framework for Tuning Parameters of Protection Mechanisms in Trustworthy Federated Learning.
ACM Trans. Intell. Syst. Technol., June, 2024
ACM Trans. Intell. Syst. Technol., June, 2024
Corrigendum to "Improved Algorithm for Permutation Testing" [Theoretical Computer Science 986 (2024) 114316].
Theor. Comput. Sci., 2024
MC-CoT: A Modular Collaborative CoT Framework for Zero-shot Medical-VQA with LLM and MLLM Integration.
CoRR, 2024
Theoretical Analysis of Privacy Leakage in Trustworthy Federated Learning: A Perspective from Linear Algebra and Optimization Theory.
CoRR, 2024
A Unified Learn-to-Distort-Data Framework for Privacy-Utility Trade-off in Trustworthy Federated Learning.
CoRR, 2024
VulDetectBench: Evaluating the Deep Capability of Vulnerability Detection with Large Language Models.
CoRR, 2024
CoRR, 2024
Deciphering the Interplay between Local Differential Privacy, Average Bayesian Privacy, and Maximum Bayesian Privacy.
CoRR, 2024
Reinforcement Learning as a Catalyst for Robust and Fair Federated Learning: Deciphering the Dynamics of Client Contributions.
CoRR, 2024
Secure Dataset Condensation for Privacy-Preserving and Efficient Vertical Federated Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024
Model Trip: Enhancing Privacy and Fairness in Model Fusion Across Multi-Federations for Trustworthy Global Healthcare.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024
2023
ACM Trans. Intell. Syst. Technol., December, 2023
ACM Trans. Intell. Syst. Technol., February, 2023
K-ESConv: Knowledge Injection for Emotional Support Dialogue Systems via Prompt Learning.
CoRR, 2023
CoRR, 2023
CoRR, 2023
Towards Achieving Near-optimal Utility for Privacy-Preserving Federated Learning via Data Generation and Parameter Distortion.
CoRR, 2023
Proceedings of the Emerging Information Security and Applications, 2023
2022
CoRR, 2022
2021
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021
Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously.
Proceedings of the 38th International Conference on Machine Learning, 2021
2020
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019