1 citations · 1 across the 5 of their papers we have counts for
5 papers
DifFRACT: Diffusion Feature Reconstruction and Attribution for Circuit Tracing
Artyom Mazur, Nina Konovalova, Aibek Alanov
While transcoder-based circuit tracing has recently enabled detailed causal analyses of large language models, it remains unclear how semantic information propagates across denoisi…
SHIFT: Steering Hidden Intermediates in Flow Transformers
Nina Konovalova, Andrey Kuznetsov, Aibek Alanov
Diffusion models have become leading approaches for high-fidelity image generation. Recent DiT-based diffusion models, in particular, achieve strong prompt adherence while producin…
Heeding the Inner Voice: Aligning ControlNet Training via Intermediate Features Feedback
Nina Konovalova, Maxim Nikolaev, Andrey Kuznetsov +1
Despite significant progress in text-to-image diffusion models, achieving precise spatial control over generated outputs remains challenging. ControlNet addresses this by introduci…
DepthART: Monocular Depth Estimation as Autoregressive Refinement Task
Bulat Gabdullin, Nina Konovalova, Nikolay Patakin +2
Monocular depth estimation has seen significant advances through discriminative approaches, yet their performance remains constrained by the limitations of training datasets. While…
A3D: Does Diffusion Dream about 3D Alignment?
Savva Ignatyev, Nina Konovalova, Daniil Selikhanovych +9
We tackle the problem of text-driven 3D generation from a geometry alignment perspective. Given a set of text prompts, we aim to generate a collection of objects with semantically…