1 citations · 1 across the 2 of their papers we have counts for
5 papers
Automating Steering for Safe Multimodal Large Language Models
Lyucheng Wu, Mengru Wang, Ziwen Xu +4
Recent progress in Multimodal Large Language Models (MLLMs) has unlocked powerful cross-modal reasoning abilities, but also raised new safety concerns, particularly when faced with…
GuardReasoner-VL: Safeguarding VLMs via Reinforced Reasoning
Yue Liu, Shengfang Zhai, Mingzhe Du +9
To enhance the safety of VLMs, this paper introduces a novel reasoning-based VLM guard model dubbed GuardReasoner-VL. The core idea is to incentivize the guard model to deliberativ…
Words or Vision: Do Vision-Language Models Have Blind Faith in Text?
Ailin Deng, Tri Cao, Zhirui Chen +1
Vision-Language Models (VLMs) excel in integrating visual and textual information for vision-centric tasks, but their handling of inconsistencies between modalities is underexplore…
PhishIntel: Toward Practical Deployment of Reference-Based Phishing Detection
Yuexin Li, Hiok Kuek Tan, Qiaoran Meng +6
Phishing is a critical cyber threat, exploiting deceptive tactics to compromise victims and cause significant financial losses. While reference-based phishing detectors (RBPDs) hav…
Are Anomaly Scores Telling the Whole Story? A Benchmark for Multilevel Anomaly Detection
Tri Cao, Minh-Huy Trinh, Ailin Deng +4
Anomaly detection (AD) is a machine learning task that identifies anomalies by learning patterns from normal training data. In many real-world scenarios, anomalies vary in severity…