Papers by Evelina Mironova

2 papers
RusCode: Russian Cultural Code Benchmark for Text-to-Image Generation (2025.findings-naacl)

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Challenge: Text-to-image generation models exhibit a strong bias toward English-speaking cultures, ignoring or misrepresenting the unique characteristics of other language groups, countries, and nationalities.
Approach: They propose a RusCode benchmark to evaluate the quality of text-to-image generation containing elements of the Russian cultural code.
Outcome: The proposed model is based on 1250 text prompts in Russian and their translations into English.
Kandinsky 3: Text-to-Image Synthesis for Multifunctional Generative Framework (2024.emnlp-demo)

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Challenge: Text-to-image (T2I) diffusion models are popular for image manipulation, but also for video generation.
Approach: They propose a novel T2I diffusion model based on latent diffusion that extends the base model for various applications.
Outcome: The proposed model achieves high quality and photorealism and is 3 times faster than the base model.

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