26 citations · 41 across the 6 of their papers we have counts for
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cs.LG2026
Detecting Hidden ML Training With Zero-Overhead Telemetry
Robi Rahman, Sabiha Tajdari
Hardware-enabled monitoring of GPU workloads underpins many proposals for AI compute governance, but if developers can defeat monitoring mechanisms, such schemes are unworkable. We…
cs.CY2026
Prioritization of Risks from Artificial Intelligence: A Delphi Study of 272 International Experts
Alexander K. Saeri, Jess Graham, Michael Noetel +185
Artificial intelligence poses many risks, ranging from familiar present-day harms to unprecedented and potentially catastrophic ones. Effective risk management requires prioritizat…
cs.CY2026
Does Distributed Training Undermine Compute Governance?
Robi Rahman
Compute governance proposals often rely on the assumption that frontier AI training requires large, detectable computing clusters. However, recent advances in distributed training…