collaborators

12 papers

cs.LG2026

Beyond Accuracy: Interpreting Topic Representation in Suicide Ideation Detection Models

Hamideh Ghanadian, Isar Nejadgholi, Hussein Al Osman

Suicide ideation detection models are typically evaluated using aggregate performance metrics, yet little is known about how they internally represent psychologically meaningful ri…

cs.AI2026

CIRCLE: A Framework for Evaluating AI from a Real-World Lens

Reva Schwartz, Carina Westling, Morgan Briggs +12

This paper proposes CIRCLE, a six-stage, lifecycle-based framework to bridge the reality gap between model-centric performance metrics and AI's materialized outcomes in deployment.…

cs.AI2026

Improving Methodologies for LLM Evaluations Across Global Languages

Akriti Vij, Benjamin Chua, Darshini Ramiah +43

As frontier AI models are deployed globally, it is essential that their behaviour remains safe and reliable across diverse linguistic and cultural contexts. To examine how current…

cs.AI2026

Improving Methodologies for Agentic Evaluations Across Domains: Leakage of Sensitive Information, Fraud and Cybersecurity Threats

Ee Wei Seah, Yongsen Zheng, Naga Nikshith +67

The rapid rise of autonomous AI systems and advancements in agent capabilities are introducing new risks due to reduced oversight of real-world interactions. Yet agent testing rema…

cs.CY2025

Social and Ethical Risks Posed by General-Purpose LLMs for Settling Newcomers in Canada

Isar Nejadgholi, Maryam Molamohammadi, Samir Bakhtawar

The non-profit settlement sector in Canada supports newcomers in achieving successful integration. This sector faces increasing operational pressures amidst rising immigration targ…

cs.CV2025

WildFireCan-MMD: A Multimodal Dataset for Classification of User-Generated Content During Wildfires in Canada

Braeden Sherritt, Isar Nejadgholi, Efstratios Aivaliotis +2

Rapid information access is vital during wildfires, yet traditional data sources are slow and costly. Social media offers real-time updates, but extracting relevant insights remain…