46 citations · 99 across the 27 of their papers we have counts for
31 papers
QwenSafe: Multimodal Content Rating Description Identification via Preference-Aligned VLMs
Dishanika Denipitiyage, Aruna Seneviratne, Suranga Seneviratne
Mobile app marketplaces require developers to disclose standardized content rating descriptors (CRDs) to inform users about potentially sensitive or restricted content. Ensuring th…
Eliciting Least-to-Most Reasoning for Phishing URL Detection
Holly Trikilis, Pasindu Marasinghe, Fariza Rashid +1
Phishing continues to be one of the most prevalent attack vectors, making accurate classification of phishing URLs essential. Recently, large language models (LLMs) have demonstrat…
RankOOD -- Class Ranking-based Out-of-Distribution Detection
Dishanika Denipitiyage, Naveen Karunanayake, Suranga Seneviratne +1
We propose RankOOD, a rank-based Out-of-Distribution (OOD) detection approach based on training a model with the Placket-Luce loss, which is now extensively used for preference ali…
Personalizing Federated Learning for Hierarchical Edge Networks with Non-IID Data
Seunghyun Lee, Omid Tavallaie, Shuaijun Chen +4
Accommodating edge networks between IoT devices and the cloud server in Hierarchical Federated Learning (HFL) enhances communication efficiency without compromising data privacy. H…
BERTDetect: A Neural Topic Modelling Approach for Android Malware Detection
Nishavi Ranaweera, Jiarui Xu, Suranga Seneviratne +1
Web access today occurs predominantly through mobile devices, with Android representing a significant share of the mobile device market. This widespread usage makes Android a prime…
A Framework to Assess Multilingual Vulnerabilities of LLMs
Likai Tang, Niruth Bogahawatta, Yasod Ginige +4
Large Language Models (LLMs) are acquiring a wider range of capabilities, including understanding and responding in multiple languages. While they undergo safety training to preven…