Regulatory Compliance
Regulatory compliance, encompassing adherence to rules and standards across diverse sectors, is a rapidly evolving field driven by the increasing use of AI and automation. Current research focuses on automating compliance checks using techniques like Large Language Models (LLMs) for analyzing legal texts and generating compliant outputs, as well as developing robust algorithms for handling incomplete or noisy data in various applications, from product classification to robotic manipulation. This work is crucial for mitigating risks, improving efficiency, and ensuring responsible technological development across industries, from finance and healthcare to manufacturing and social media.
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Papers
March 7, 2025
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February 7, 2025
February 3, 2025
Standardizing Intelligence: Aligning Generative AI for Regulatory and Operational Compliance
Joseph Marvin Imperial, Matthew D. Jones, Harish Tayyar MadabushiCompliance while resisting: a shear-thickening fluid controller for physical human-robot interaction
Lu Chen, Lipeng Chen, Xiangchi Chen, Haojian Lu, Yu Zheng, Jun Wu, Yue Wang, Zhengyou Zhang, Rong XiongComply: Learning Sentences with Complex Weights inspired by Fruit Fly Olfaction
Alexei Figueroa, Justus Westerhoff, Atefi Golzar, Dennis Fast, Benjamin Winter, Felix Alexader Gers, Alexander Löser, Wolfang NejdlBeyond Yes or No: Predictive Compliance Monitoring Approaches for Quantifying the Magnitude of Compliance Violations
Qian Chen, Stefanie Rinderle-Ma, Lijie Wen
January 23, 2025