3 citations · 3 across the 5 of their papers we have counts for
5 papers
AssurAI: Experience with Constructing Korean Socio-cultural Datasets to Discover Potential Risks of Generative AI
Chae-Gyun Lim, Seung-Ho Han, EunYoung Byun +51
The rapid evolution of generative AI necessitates robust safety evaluations. However, current safety datasets are predominantly English-centric, failing to capture specific risks i…
SAIF: A Comprehensive Framework for Evaluating the Risks of Generative AI in the Public Sector
Kyeongryul Lee, Heehyeon Kim, Joyce Jiyoung Whang
The rapid adoption of generative AI in the public sector, encompassing diverse applications ranging from automated public assistance to welfare services and immigration processes,…
Unveiling the Threat of Fraud Gangs to Graph Neural Networks: Multi-Target Graph Injection Attacks Against GNN-Based Fraud Detectors
Jinhyeok Choi, Heehyeon Kim, Joyce Jiyoung Whang
Graph neural networks (GNNs) have emerged as an effective tool for fraud detection, identifying fraudulent users, and uncovering malicious behaviors. However, attacks against GNN-b…
SpoT-Mamba: Learning Long-Range Dependency on Spatio-Temporal Graphs with Selective State Spaces
Jinhyeok Choi, Heehyeon Kim, Minhyeong An +1
Spatio-temporal graph (STG) forecasting is a critical task with extensive applications in the real world, including traffic and weather forecasting. Although several recent methods…
Dynamic Relation-Attentive Graph Neural Networks for Fraud Detection
Heehyeon Kim, Jinhyeok Choi, Joyce Jiyoung Whang
Fraud detection aims to discover fraudsters deceiving other users by, for example, leaving fake reviews or making abnormal transactions. Graph-based fraud detection methods conside…