2 citations · 11 across the 12 of their papers we have counts for
13 papers
GHOST 2.0: generative high-fidelity one shot transfer of heads
Alexander Groshev, Anastasiia Iashchenko, Pavel Paramonov +2
While the task of face swapping has recently gained attention in the research community, a related problem of head swapping remains largely unexplored. In addition to skin color tr…
Unleashing the power of novel conditional generative approaches for new materials discovery
Lev Novitskiy, Vladimir Lazarev, Mikhail Tiutiulnikov +6
For a very long time, computational approaches to the design of new materials have relied on an iterative process of finding a candidate material and modeling its properties. AI ha…
Kandinsky 3: Text-to-Image Synthesis for Multifunctional Generative Framework
Vladimir Arkhipkin, Viacheslav Vasilev, Andrei Filatov +9
Text-to-image (T2I) diffusion models are popular for introducing image manipulation methods, such as editing, image fusion, inpainting, etc. At the same time, image-to-video (I2V)…
ESQA: Event Sequences Question Answering
Irina Abdullaeva, Andrei Filatov, Mikhail Orlov +6
Event sequences (ESs) arise in many practical domains including finance, retail, social networks, and healthcare. In the context of machine learning, event sequences can be seen as…
Your Transformer is Secretly Linear
Anton Razzhigaev, Matvey Mikhalchuk, Elizaveta Goncharova +4
This paper reveals a novel linear characteristic exclusive to transformer decoders, including models such as GPT, LLaMA, OPT, BLOOM and others. We analyze embedding transformations…
OmniFusion Technical Report
Elizaveta Goncharova, Anton Razzhigaev, Matvey Mikhalchuk +6
Last year, multimodal architectures served up a revolution in AI-based approaches and solutions, extending the capabilities of large language models (LLM). We propose an \textit{Om…
FusionFrames: Efficient Architectural Aspects for Text-to-Video Generation Pipeline
Vladimir Arkhipkin, Zein Shaheen, Viacheslav Vasilev +3
Multimedia generation approaches occupy a prominent place in artificial intelligence research. Text-to-image models achieved high-quality results over the last few years. However,…
Kandinsky 3.0 Technical Report
Vladimir Arkhipkin, Andrei Filatov, Viacheslav Vasilev +6
We present Kandinsky 3.0, a large-scale text-to-image generation model based on latent diffusion, continuing the series of text-to-image Kandinsky models and reflecting our progres…
The Shape of Learning: Anisotropy and Intrinsic Dimensions in Transformer-Based Models
Anton Razzhigaev, Matvey Mikhalchuk, Elizaveta Goncharova +3
In this study, we present an investigation into the anisotropy dynamics and intrinsic dimension of embeddings in transformer architectures, focusing on the dichotomy between encode…
Kandinsky: an Improved Text-to-Image Synthesis with Image Prior and Latent Diffusion
Anton Razzhigaev, Arseniy Shakhmatov, Anastasia Maltseva +7
Text-to-image generation is a significant domain in modern computer vision and has achieved substantial improvements through the evolution of generative architectures. Among these,…
RusTitW: Russian Language Text Dataset for Visual Text in-the-Wild Recognition
Igor Markov, Sergey Nesteruk, Andrey Kuznetsov +1
Information surrounds people in modern life. Text is a very efficient type of information that people use for communication for centuries. However, automated text-in-the-wild recog…
RuCLIP -- new models and experiments: a technical report
Alex Shonenkov, Andrey Kuznetsov, Denis Dimitrov +10
In the report we propose six new implementations of ruCLIP model trained on our 240M pairs. The accuracy results are compared with original CLIP model with Ru-En translation (OPUS-…
Many Heads but One Brain: Fusion Brain -- a Competition and a Single Multimodal Multitask Architecture
Daria Bakshandaeva, Denis Dimitrov, Vladimir Arkhipkin +8
Supporting the current trend in the AI community, we present the AI Journey 2021 Challenge called Fusion Brain, the first competition which is targeted to make the universal archit…