1 citations · 1 across the 5 of their papers we have counts for
7 papers
FraudBench: Protocol-Sensitive Benchmarking of Adversarial Robustness for Financial Risk Assessment
Xitong Zeng, Zhaoge Bi, Yitian Yang +2
Machine learning models are widely used in financial fraud and credit-risk detection, yet their adversarial robustness remains difficult to evaluate because financial tabular data…
When AI Meets Wall Street: A Survey on Trustworthy AI in Fintech
Qingwen Zeng, Zhenghao Zhao, Yitian Yang +6
Artificial intelligence is now embedded as a primary decision engine in continuously operated financial AI pipelines spanning training and updating, deployment and inference, and o…
Engineering Carbon Credits Towards A Responsible FinTech Era: The Practices, Implications, and Future
Qingwen Zeng, Hanlin Xu, Nanjun Xu +5
Carbon emissions significantly contribute to climate change, and carbon credits have emerged as a key tool for mitigating environmental damage and helping organizations manage thei…
Threats and Defenses in Federated Learning Life Cycle: A Comprehensive Survey and Challenges
Yanli Li, Zhongliang Guo, Nan Yang +3
Federated Learning (FL) offers innovative solutions for privacy-preserving collaborative machine learning (ML). Despite its promising potential, FL is vulnerable to various attacks…
Fairpriori: Improving Biased Subgroup Discovery for Deep Neural Network Fairness
Kacy Zhou, Jiawen Wen, Nan Yang +3
While deep learning has become a core functional module of most software systems, concerns regarding the fairness of ML predictions have emerged as a significant issue that affects…
On Security Weaknesses and Vulnerabilities in Deep Learning Systems
Zhongzheng Lai, Huaming Chen, Ruoxi Sun +3
The security guarantee of AI-enabled software systems (particularly using deep learning techniques as a functional core) is pivotal against the adversarial attacks exploiting softw…