Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale.
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CoRR, February, 2025
Position: Contextual Confidence and Generative AI.
Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning, 2025
Push and Pull: A Framework for Measuring Attentional Agency on Digital Platforms.
Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, 2025
A machine-learning-based framework for contractor selection and order allocation in public construction projects considering sustainability, risk, and safety.
Ann. Oper. Res., July, 2024
Personhood credentials: Artificial intelligence and the value of privacy-preserving tools to distinguish who is real online.
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CoRR, 2024
Push and Pull: A Framework for Measuring Attentional Agency.
CoRR, 2024
Verifiable evaluations of machine learning models using zkSNARKs.
CoRR, 2024
Plural Management: A Scalable Model for Decentralized Organizational Authority Using Quadratic Voting and Prediction Markets.
Proceedings of the CENTERIS 2024 - International Conference on ENTERprise Information Systems / ProjMAN - International Conference on Project MANagement / HCist, 2024
AI and Democracy's Digital Identity Crisis.
CoRR, 2023
Sandi: A System for Accountability and Applications in Direct Communication (Extended Abstract).
CoRR, 2023
Contextual Confidence and Generative AI.
CoRR, 2023
Unsupervised Learning of Molecular Embeddings for Enhanced Clustering and Emergent Properties for Chemical Compounds.
CoRR, 2023
Face Recognition in the age of CLIP & Billion image datasets.
CoRR, 2023
A Plural Decentralized Identity Frontier: Abstraction v. Composability Tradeoffs in Web3.
CoRR, 2022
NFT Appraisal Prediction: Utilizing Search Trends, Public Market Data, Linear Regression and Recurrent Neural Networks.
CoRR, 2022