2 citations · 5 across the 10 of their papers we have counts for
10 papers
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…
Tactile Genesis: Exploring Tactile Sensors at Scale for Learning Dexterous Tasks
Trinity Chung, Kashu Yamazaki, Dhruv Patel +4
Tactile sensing is critical for contact-rich dexterous manipulation, yet it remains unclear which tactile abstractions a policy needs and when richer tactile fields justify their h…
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…
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…
Core Safety Values for Provably Corrigible Agents
Aran Nayebi
We introduce the first complete formal solution to corrigibility in the off-switch game, with provable guarantees in multi-step, partially observed environments. Our framework cons…
Intrinsic Goals for Autonomous Agents: Model-Based Exploration in Virtual Zebrafish Predicts Ethological Behavior and Whole-Brain Dynamics
Reece Keller, Alyn Kirsch, Felix Pei +3
Autonomy is a hallmark of animal intelligence, enabling adaptive and intelligent behavior in complex environments without relying on external reward or task structure. Existing rei…
When Do AI Gains Become Broadly Shareable? A Policy Threshold for AI-Driven Automation
Aran Nayebi
AI-driven automation generates broad-based social benefit only if technical gains become visible, durable, and publicly claimable. We develop a policy-facing stress test by extendi…
Brain-Model Evaluations Need the NeuroAI Turing Test
Jenelle Feather, Meenakshi Khosla, N. Apurva Ratan Murty +1
What makes an artificial system a good model of intelligence? The classical test proposed by Alan Turing focuses on behavior, requiring that an artificial agent's behavior be indis…
Intrinsic Barriers and Practical Pathways for Human-AI Alignment: An Agreement-Based Complexity Analysis
Aran Nayebi
We formalize AI alignment as a multi-objective optimization problem called -agreement, in which a set of agents (including humans) must reach…
A Goal-Driven Approach to Systems Neuroscience
Aran Nayebi
Humans and animals exhibit a range of interesting behaviors in dynamic environments, and it is unclear how our brains actively reformat this dense sensory information to enable the…