Zonghao Ying
Orcid: 0000-0002-7249-579X
According to our database1,
Zonghao Ying authored at least 35 papers
between 2021 and 2026.
Collaborative distances:
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Bibliography
2026
DMN: A Compositional Framework for Jailbreaking Multimodal LLMs with Multi-Image Inputs.
CoRR, May, 2026
CoRR, May, 2026
CoRR, May, 2026
CoRR, May, 2026
TrajShield: Trajectory-Level Safety Mediation for Defending Text-to-Video Models Against Jailbreak Attacks.
CoRR, May, 2026
AgentVisor: Defending LLM Agents Against Prompt Injection via Semantic Virtualization.
CoRR, April, 2026
Uncovering Security Threats and Architecting Defenses in Autonomous Agents: A Case Study of OpenClaw.
CoRR, March, 2026
Reasoning-Oriented Programming: Chaining Semantic Gadgets to Jailbreak Large Vision Language Models.
CoRR, March, 2026
CoRR, March, 2026
Int. J. Comput. Vis., January, 2026
DIVER: Dynamic Iterative Visual Evidence Reasoning for Multimodal Fake News Detection.
CoRR, January, 2026
IEEE Trans. Dependable Secur. Comput., 2026
2025
CoRR, December, 2025
Disentangling Fact from Sentiment: A Dynamic Conflict-Consensus Framework for Multimodal Fake News Detection.
CoRR, December, 2025
VEIL: Jailbreaking Text-to-Video Models via Visual Exploitation from Implicit Language.
CoRR, November, 2025
Sequential Comics for Jailbreaking Multimodal Large Language Models via Structured Visual Storytelling.
CoRR, October, 2025
CoRR, October, 2025
Detoxifying Large Language Models via Autoregressive Reward Guided Representation Editing.
CoRR, October, 2025
CoRR, September, 2025
CoRR, June, 2025
CoRR, June, 2025
Towards Understanding the Safety Boundaries of DeepSeek Models: Evaluation and Findings.
CoRR, March, 2025
IEEE Trans. Inf. Forensics Secur., 2025
Proceedings of the 33rd ACM International Conference on Multimedia, 2025
Reasoning-Augmented Conversation for Multi-Turn Jailbreak Attacks on Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025
2024
CoRR, 2024
CoRR, 2024
2023
Cybersecur., December, 2023
DLP: towards active defense against backdoor attacks with decoupled learning process.
Cybersecur., December, 2023
2021
DeeSCVHunter: A Deep Learning-Based Framework for Smart Contract Vulnerability Detection.
Proceedings of the International Joint Conference on Neural Networks, 2021