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ЖУРНАЛЫ // Компьютерная оптика // Архив

Компьютерная оптика, 2023, том 47, выпуск 1, страницы 185–195 (Mi co1116)

ЧИСЛЕННЫЕ МЕТОДЫ И АНАЛИЗ ДАННЫХ

Many heads but one brain: FusionBrain – a single multimodal multitask architecture and a competition

D. D. Bakshandaevaab, D. V. Dimitrovcad, V. S. Arkhipkina, A. V. Shonenkovd, M. S. Potanind, D. K. Karachevd, A. V. Kuznetsovade, A. D. Voronovd, A. A. Petiushkod, V. F. Davydovaa, E. V. Tutubalinaadf

a Sber AI
b University of Helsinki
c Lomonosov Moscow State University
d Artificial Intelligence Research Institute, Moscow
e Samara National Research University
f National Research University Higher School of Economics, Moscow

Аннотация: Supporting the current trend in the AI community, we present the AI Journey 2021 Challenge called FusionBrain, the first competition which is targeted to make a universal architecture which could process different modalities (in this case, images, texts, and code) and solve multiple tasks for vision and language. The FusionBrain Challenge combines the following specific tasks: Code2code Translation, Handwritten Text recognition, Zero-shot Object Detection, and Visual Question Answering. We have created datasets for each task to test the participants’ submissions on it. Moreover, we have collected and made publicly available a new handwritten dataset in both English and Russian, which consists of 94,128 pairs of images and texts. We also propose a multimodal and multitask architecture – a baseline solution, in the centre of which is a frozen foundation model and which has been trained in Fusion mode along with Single-task mode. The proposed Fusion approach proves to be competitive and more energy-efficient compared to the task-specific one.

Ключевые слова: multimodality, multitask, bilinguality, foundation models, FusionBrain challenge

Поступила в редакцию: 08.09.2022
Принята в печать: 21.11.2022

Язык публикации: английский

DOI: 10.18287/2412-6179-CO-1220



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