Artificial Intelligence (AI) is transforming the fight against financial crime, but how can it be deployed responsibly? In answer to that question, this book provides a comprehensive roadmap that integrates legal clarity, ethical guidance, and operational strategies on AI governance. Leveraging the EU's AI Act, national legal instruments and comparative insights, the book examines the challenges of AI governance and offers practical tools for bias mitigation, explainability, accountability, and risk management. The book's use of real-world case studies and contributions from academics and practitioners – including experts with law enforcement experience – enables scholars, students, and professionals in disciplines such as law, criminology, finance, and policing to bridge theory and practice. This makes it an indispensable resource for research, teaching, and professional training. Whether you are shaping policy, implementing compliance frameworks, or exploring AI's role in fighting financial crime, this book provides the roadmap you need to balance innovation and responsibility. This title is also available as open access on Cambridge Core.
GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations...
Xiaotian Zhang, Chun-yan Li, Yi Zong et al.· arXiv.org· 216 citations· ⚡17
This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.
This paper presents a comprehensive overview of the Ultralytics YOLO family, emphasizing architectural evolution, benchmarking, deployment, and emerging directions from YOLOv5 through YOLO27, and examines detection, segmentation, depth, classification, pose, oriented detection, tracking, export, quantization, and deplo...
Empirically, PRISM reduces the end-to-end time for data selection and model tuning to just 30% of conventional pipelines, and achieves this efficiency while simultaneously enhancing performance, surpassing models fine-tuned on the full dataset across eight multimodal and three language understanding benchmarks.
Jinhe Bi, Yifan Wang, Danqi Yan et al.· arXiv.org· 73 citations· ⚡4
This paper proposes adaptive sampling with approximate expected futures (ASAp), a decoding algorithm that guarantees the output to be grammatical while provably producing outputs that match the conditional probability of the LLM's distribution conditioned on the given grammar constraint.
Kanghee Park, Jiayu Wang, Taylor Berg-Kirkpatrick et al.· Neural Information Processin...· 70 citations· ⚡5
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
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With $2.1 million funding from Google.org, the open-source Public Transit Intelligence Hub will unify public transit monitoring, operations, and passenger communication.
