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20212025
most citedUnleashing the power of novel conditional generative approaches for new materials discovery

2 citations · 11 across the 12 of their papers we have counts for

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5 papers · 1 filter

cond-mat.mtrl-sci2024★ 2 cited

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…

cs.CV2024

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)…

cs.CL2024

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…

cs.LG2024

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…

cs.CV2024★ 2 cited

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…