2 papers
cs.LG2025
Hybrid Data can Enhance the Utility of Synthetic Data for Training Anti-Money Laundering Models
Rachel Chung, Pratyush Nidhi Sharma, Mikko Siponen +2
Money laundering is a critical global issue for financial institutions. Automated Anti-money laundering (AML) models, like Graph Neural Networks (GNN), can be trained to identify i…
cs.SE2025
DevLicOps: A Framework for Mitigating Licensing Risks in AI-Generated Code
Pratyush Nidhi Sharma, Lauren Wright, Anne Herfurth +4
Generative AI coding assistants (ACAs) are widely adopted yet pose serious legal and compliance risks. ACAs can generate code governed by restrictive open-source licenses (e.g., GP…