AIConfPaper
← Search

Mikhail Terekhov

4 accepted papers

2026

Adaptive Attacks on Trusted Monitors Subvert AI Control Protocols

Mikhail Terekhov, Alexander Panfilov, Daniil Dzenhaliou, Caglar Gulcehre, Maksym Andriushchenko, Ameya Prabhu +1
ICLR 2026poster

AI control protocols serve as a defense mechanism to stop untrusted LLM agents from causing harm in autonomous settings. Prior work treats this as a security problem, stress testing with exploits that use the deployment context to subtly complete harmful side tasks, such as backdoor insertion. In pr…

Cited by 0Source ↗Scholar ↗
2026

Control Tax: The Price of Keeping AI in Check

Mikhail Terekhov, Zhen Ning David Liu, Caglar Gulcehre, Samuel Albanie
ICLR 2026poster

The rapid integration of agentic AI into high-stakes real-world applications requires robust oversight mechanisms. The emerging field of AI Control (AIC) aims to provide such an oversight mechanism, but practical adoption depends heavily on implementation overhead. To study this problem better, we i…

Cited by 0Source ↗code ↗Scholar ↗
2025

One-Step is Enough: Sparse Autoencoders for Text-to-Image Diffusion Models

Viacheslav Surkov, Chris Wendler, Antonio Mari, Mikhail Terekhov, Justin Deschenaux, Robert West +2
NeurIPS 2025poster

For large language models (LLMs), sparse autoencoders (SAEs) have been shown to decompose intermediate representations that often are not interpretable directly into sparse sums of interpretable features, facilitating better control and subsequent analysis. However, similar analyses and approaches h…

Cited by 30Source ↗Scholar ↗
2023

Tangent Sampson Error: Fast Approximate Two-view Reprojection Error for Central Camera Models

Mikhail Terekhov, Viktor Larsson
ICCV 2023poster

In this paper we introduce the Tangent Sampson error, which is a generalization of the classical Sampson error in two-view geometry that allows for arbitrary central camera models. It only requires local gradients of the distortion map at the original correspondences (allowing for pre-computation) r…

Cited by 4PDF ↗Scholar ↗