Zhibo Jin

Orcid: 0009-0003-0218-1941

According to our database1, Zhibo Jin authored at least 19 papers between 2023 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

On csauthors.net:

Bibliography

2024
A Vision-Transformer-Based Convex Variational Network for Bridge Pavement Defect Segmentation.
IEEE Trans. Intell. Transp. Syst., October, 2024

Enhancing Transferability of Adversarial Attacks with GE-AdvGAN+: A Comprehensive Framework for Gradient Editing.
CoRR, 2024

Leveraging Information Consistency in Frequency and Spatial Domain for Adversarial Attacks.
CoRR, 2024

Enhancing Adversarial Attacks via Parameter Adaptive Adversarial Attack.
CoRR, 2024

DMS: Addressing Information Loss with More Steps for Pragmatic Adversarial Attacks.
CoRR, 2024

Benchmarking Transferable Adversarial Attacks.
CoRR, 2024

GE-AdvGAN: Improving the transferability of adversarial samples by gradient editing-based adversarial generative model.
Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

Leveraging Information Consistency in Frequency and Spatial Domain for Adversarial Attacks.
Proceedings of the PRICAI 2024: Trends in Artificial Intelligence, 2024

Enhancing Model Interpretability with Local Attribution over Global Exploration.
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

Iterative Search Attribution for Deep Neural Networks.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

AttEXplore: Attribution for Explanation with model parameters eXploration.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Enhancing Transferable Adversarial Attacks on Vision Transformers through Gradient Normalization Scaling and High-Frequency Adaptation.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Improving Adversarial Transferability via Frequency-Guided Sample Relevance Attack.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

MFABA: A More Faithful and Accelerated Boundary-Based Attribution Method for Deep Neural Networks.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Towards Minimising Perturbation Rate for Adversarial Machine Learning with Pruning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Improving Adversarial Transferability via Frequency-based Stationary Point Search.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

FVW: Finding Valuable Weight on Deep Neural Network for Model Pruning.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

POSTER: ML-Compass: A Comprehensive Assessment Framework for Machine Learning Models.
Proceedings of the 2023 ACM Asia Conference on Computer and Communications Security, 2023

DANAA: Towards Transferable Attacks with Double Adversarial Neuron Attribution.
Proceedings of the Advanced Data Mining and Applications - 19th International Conference, 2023


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