4 papers
RISE: Red-teaming via Iterative Strategy Evolution for Modern Text-to-Image Models
Dmitrii Kharlapenko, Sergei Bratchikov, Konstantin Korolev +1
On modern production text-to-image systems, successful policy violations are rare, and previously effective human-written seeds are often patched out. Current automated red-teamers…
Fluid Reasoning Representations
Dmitrii Kharlapenko, Terry Jingchen Zhang, Arth Singh +4
Frontier large language models increasingly solve complex tasks involving abstract concepts through extended test-time thinking. Yet we lack a mechanistic account of how extended t…
Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning
Stepan Shabalin, Ayush Panda, Dmitrii Kharlapenko +3
Sparse autoencoders are a promising new approach for decomposing language model activations for interpretation and control. They have been applied successfully to vision transforme…
Scaling sparse feature circuit finding for in-context learning
Dmitrii Kharlapenko, Stepan Shabalin, Fazl Barez +2
Sparse autoencoders (SAEs) are a popular tool for interpreting large language model activations, but their utility in addressing open questions in interpretability remains unclear.…