Get started
Author

Zhenhong Zhou

Observed name: Zhou, Zhenhong
Observed institution: Nanyang Technological University
OpenAlex ID: A5122199794
In-Place Instruction Following in Diffusion Language Models
2026 · Nie, Zheng, Li, Zherui, et al. · arXiv (Cornell University)
PDF
From Inaudible Inputs to Model Failures: Low-Frequency Safety Risks in LALMs
2026 · Zhang, Yuanhe, Wang, Weiliu, et al. · arXiv (Cornell University)
PDF
Structure-Guided Visual Perturbation Neutralization for LVLMs
2026 · Zhang, Yuanhe, Wang, Xueting, et al. · arXiv (Cornell University)
PDF
A Survey of Large Audio Language Models: Generalization, Trustworthiness, and Outlook
2026 · Luo, Kaiwen, Zhou, Zhenhong, et al. · arXiv (Cornell University)
PDF
Explaining and Breaking the Safety-Helpfulness Ceiling via Preference Dimensional Expansion
2026 · Huang, ShiYing, Lin, Liang, et al. · arXiv (Cornell University)
PDF
SafeSeek: Universal Attribution of Safety Circuits in Language Models
2026 · Yu, Miao, Fu, Siyuan, et al. · arXiv (Cornell University)
PDF
LARFT: Closing the Cognition-Action Gap for Length Instruction Following in Large Language Models
2026 · Zhang, Wei, Du, Lintong, et al. · arXiv (Cornell University)
PDF
Omni-Safety under Cross-Modality Conflict: Vulnerabilities, Dynamics Mechanisms and Efficient Alignment
2026 · Wang, Kun, Li, Zherui, et al. · arXiv (Cornell University)
PDF
RECUR: Resource Exhaustion Attack via Recursive-Entropy Guided Counterfactual Utilization and Reflection
2026 · Wang, Ziwei, Zhang, Yuanhe, et al. · arXiv (Cornell University)
PDF
RSA-Bench: Benchmarking Audio Large Models in Real-World Acoustic Scenarios
2026 · Zhang, Yibo, Lin, Liang, et al. · arXiv (Cornell University)
PDF
SEE: Signal Embedding Energy for Quantifying Noise Interference in Large Audio Language Models
2026 · Zhang, Yuanhe, Tian, Jiayu, et al. · arXiv (Cornell University)
PDF
ChronosAudio: A Comprehensive Long-Audio Benchmark for Evaluating Audio-Large Language Models
2026 · Luo, Kaiwen, Lin, Liang, et al. · arXiv (Cornell University)
PDF
HearSay Benchmark: Do Audio LLMs Leak What They Hear?
2026 · Wang, Jin, Lin, Liang, et al. · arXiv (Cornell University)
PDF
CSSBench: Evaluating the Safety of Lightweight LLMs against Chinese-Specific Adversarial Patterns
2026 · Zhou, Zhenhong, Yan, Shilinlu, et al. · arXiv (Cornell University)
PDF
Resource Consumption Threats in Large Language Models: A Survey
2026 · Yuanhe Zhang, Xinyue Wang, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP)
PDF
Works count: 15
Citation count:
H-index:
I10-index:
Year
Topic
Type