collaborators

5 papers

cs.RO2026

Inspect Robots: Evaluating the Capabilities and Safety of Embodied AI

Christopher Leet, Achu Menon, Sravanthi Machcha +12

General purpose language models are increasingly able to control robotic hardware. Understanding the capabilities and safety of these models when embodied is therefore increasingly…

cs.HC2026

Refuses in Chat, Complies with Arms: LLM Refusal Does Not Survive Robot Control

Edward Sun, Christopher Leet, Sravanthi Machcha +4

Frontier language models reliably refuse to explain how to cause physical harm. We ask whether this refusal survives when the same models control a robot. We introduce RoboHarm, a…

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.CR2026

Covert Influence Between Language Models

Avidan Shah, Jay Chooi, Jinghua Ou +1

As language models increasingly consume one another's outputs, covert influence -- a phenomenon where a sender's payload (the behavioral disposition it is conditioned to propagate)…

cs.LG2025

DP-AdamW: Investigating Decoupled Weight Decay and Bias Correction in Private Deep Learning

Jay Chooi, Kevin Cong, Russell Li +1

As deep learning methods increasingly utilize sensitive data on a widespread scale, differential privacy (DP) offers formal guarantees to protect against information leakage during…