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cs.LG2026
Sharding Prevents LLM Oversight Failures and Adversarial Exploitation
Victor Akinwande, J. Zico Kolter, Aran Nayebi
Giving an LLM judge more compute does not necessarily make it check more requirements. When one call must return many verdicts, some decisions become weakly grounded in the evidenc…
cs.LG2026
ROGUE: Evaluating Corrigibility Failures in Frontier Computer-Use Agents
Jeremy Tien, Abishek Anand, Yu-Rou Tuan +3
As AI agents are increasingly deployed in real personal and corporate settings (email accounts, development workflows, company databases, etc.), safety considerations surrounding t…
cs.LG2026★ 2 cited
What Capable Agents Must Know: Selection Theorems for Robust Decision-Making under Uncertainty
Aran Nayebi
As artificial agents become increasingly capable, what internal structure is necessary for an agent to act competently under uncertainty? Classical results show that optimal contro…