4 papers
SRVAU-R1: Enhancing Video Anomaly Understanding via Reflection-Aware Learning
Zihao Zhao, Shengting Cao, Muchao Ye
Multi-modal large language models (MLLMs) have demonstrated significant progress in reasoning capabilities and shown promising effectiveness in video anomaly understanding (VAU) ta…
POLAR: Automating Cyber Threat Prioritization through LLM-Powered Assessment
Luoxi Tang, Yuqiao Meng, Ankita Patra +3
Large Language Models (LLMs) are intensively used to assist security analysts in counteracting the rapid exploitation of cyber threats, wherein LLMs offer cyber threat intelligence…
CyLens: Towards Reinventing Cyber Threat Intelligence in the Paradigm of Agentic Large Language Models
Xiaoqun Liu, Jiacheng Liang, Qiben Yan +5
The exponential growth of cyber threat knowledge, exemplified by the expansion of databases such as MITRE-CVE and NVD, poses significant challenges for cyber threat analysis. Secur…
VERA: Explainable Video Anomaly Detection via Verbalized Learning of Vision-Language Models
Muchao Ye, Weiyang Liu, Pan He
The rapid advancement of vision-language models (VLMs) has established a new paradigm in video anomaly detection (VAD): leveraging VLMs to simultaneously detect anomalies and provi…