collaborators

5 papers

cs.CV2026

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…

cs.LG2026

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…

cs.SE2026

Detecting and Characterising Mobile App Metamorphosis in Google Play Store

D. Denipitiyage, B. Silva, K. Gunathilaka +4

App markets have evolved into highly competitive and dynamic environments for developers. While the traditional app life cycle involves incremental updates for feature enhancements…

cs.AI2026

PrivPRISM: Automatically Detecting Discrepancies Between Google Play Data Safety Declarations and Developer Privacy Policies

Bhanuka Silva, Dishanika Denipitiyage, Anirban Mahanti +2

End-users seldom read verbose privacy policies, leading app stores like Google Play to mandate simplified data safety declarations as a user-friendly alternative. However, these se…

cs.LG2025

Detecting Content Rating Violations in Android Applications: A Vision-Language Approach

D. Denipitiyage, B. Silva, S. Seneviratne +2

Despite regulatory efforts to establish reliable content-rating guidelines for mobile apps, the process of assigning content ratings in the Google Play Store remains self-regulated…