Chia-Yi Hsu

Orcid: 0009-0000-7772-8735

According to our database1, Chia-Yi Hsu authored at least 24 papers between 2018 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Harmless Yet Harmful: Neutral Prompting Attacks for Stealthy Hallucination Steering in Agent Skills.
CoRR, May, 2026

Trust Me, Import This: Dependency Steering Attacks via Malicious Agent Skills.
CoRR, May, 2026

2025
DPAF: Image Synthesis via Differentially Private Aggregation in Forward Phase.
IEEE Internet Things J., March, 2025

Layer-Aware Task Arithmetic: Disentangling Task-Specific and Instruction-Following Knowledge.
CoRR, February, 2025

BADTV: Unveiling Backdoor Threats in Third-Party Task Vectors.
CoRR, January, 2025

VP-NTK: Exploring the Benefits of Visual Prompting in Differentially Private Data Synthesis.
Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

Layer-Aware Task Arithmetic: Disentangling Task-Specific and Instruction-Following Knowledge.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

2024
Safe LoRA: the Silver Lining of Reducing Safety Risks when Fine-tuning Large Language Models.
CoRR, 2024

Deepfake Detection through Temporal Attention.
Proceedings of the 33rd Wireless and Optical Communications Conference, 2024

Safe LoRA: The Silver Lining of Reducing Safety Risks when Finetuning Large Language Models.
Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Ring-A-Bell! How Reliable are Concept Removal Methods For Diffusion Models?
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Road Decals as Trojans: Disrupting Autonomous Vehicle Navigation with Adversarial Patterns.
Proceedings of the 54th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, 2024

2023
On the Private Data Synthesis Through Deep Generative Models for Data Scarcity of Industrial Internet of Things.
IEEE Trans. Ind. Informatics, 2023

2022
Real-World Adversarial Examples Via Makeup.
Proceedings of the IEEE International Conference on Acoustics, 2022

Adversarial Examples Can Be Effective Data Augmentation for Unsupervised Machine Learning.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
CAFE: Catastrophic Data Leakage in Vertical Federated Learning.
CoRR, 2021

Real-World Adversarial Examples involving Makeup Application.
CoRR, 2021

Formalizing Generalization and Robustness of Neural Networks to Weight Perturbations.
CoRR, 2021

Adversarial Examples for Unsupervised Machine Learning Models.
CoRR, 2021

Formalizing Generalization and Adversarial Robustness of Neural Networks to Weight Perturbations.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Catastrophic Data Leakage in Vertical Federated Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Non-Singular Adversarial Robustness of Neural Networks.
Proceedings of the IEEE International Conference on Acoustics, 2021

2019
Characterizing Adversarial Subspaces by Mutual Information.
Proceedings of the 2019 ACM Asia Conference on Computer and Communications Security, 2019

2018
On the Utility of Conditional Generation Based Mutual Information for Characterizing Adversarial Subspaces.
Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018


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