FusionFrames: efficient architectural aspects for text-to-video
generation pipeline
arxiv, 2023
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Kandinsky: an improved text-to-image synthesis with image prior and
latent diffusion
EMNLP 2023
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Kandinsky 3.0 technical report
arxiv, 2023
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CRAFT: Cultural Russian-oriented dataset adaptation for focused
text-to-image generation
Doklady Mathematics, 2024
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Kandinsky 3: Text-to-image synthesis for multifunctional generative
framework
EMNLP 2024
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Improveyourvideos: Architectural improvements for text-to-video
generation pipeline
IEEE Access, 2024
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RusCode: Russian Cultural Code Benchmark for Text-to-Image
Generation
NAACL 2025
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VIVAT: Virtuous Improving VAE Training through Artifact Mitigation
arxiv, 2025
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NABLA: Neighborhood Adaptive Block-Level Attention
arxiv, 2025
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Time-Correlated Video Bridge Matching
arxiv, 2025
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Publications
Here we share the results of our research and development. We are
convinced that openness
and collaboration are the foundation of progress in the field of
artificial intelligence. This section contains publications that describe
in detail the architectural solutions, teaching methods, and stages
of creating Kandinsky.
Our
Mission
Our mission is to move the industry forward by creating models and
approaches that open up new formats
of creativity, accelerate scientific discoveries, and unlock the
potential of generative AI.
About
Kandinsky Lab
We are a team of researchers, engineers, and analysts who create
state-of-the-art image and video generation models. We combine deep
expertise in machine learning, data,
and computing systems and share research, code,
and models to develop artificial intelligence together
with the community.