A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Unknown
MemGuard proposes persisting verifier signals to govern what LLM-agent memory systems store and when stored information may influence later decisions.
Nitesh V. Chawla, Paulo Benanti
Proposes a rupture test and RISE AI architecture to bound AI claims to what has been evaluated, distinguishing evidence-bounded deployment from measurement-bounded governance.
Unknown
This paper provides a comprehensive review of privacy-preserving machine learning (PPML) methods, introduces a Privacy-Utility-Governance (PGU) model for evaluating PPML systems, and discusses challenges and future directions.
Unknown
This paper provides a characterization of AI agents through profiles to support alignment and governance efforts.
Scott Thiebes, Sebastian Lins, Ali Sunyaev
Introduces Trustworthy AI (TAI) with five foundational principles and a data-driven research framework for future AI governance.
Michael Rogerson, Glenn Parry
This paper uses qualitative case studies to show blockchain enhances supply chain visibility and trust, but faces challenges in technology trust, human error, governance, and consumer willingness to pay.
Noam Kolt
This paper identifies and characterizes problems arising from AI agents, including issues of information, to inform governance.