Отрывок: 01), the final result can range from 0 to 4. We also measured the performance of state-of-the-art single-task models – PLBART [52], Easter2 [53], MDETR [48] – for each of the subtasks on our private test sets (see Table 4). It should be noted that the vast majority of models (including the state-of-the-art one) s...
Название : Many heads but one brain: FusionBrain – a single multimodal multitask architecture and a competition
Авторы/Редакторы : Bakshandaeva, D.D.
Dimitrov, D.V.
Arkhipkin, V.S.
Shonenkov, A.V.
Potanin, M.S.
Karachev, D.K.
Kuznetsov, A.V.
Voronov, A.D.
Petiushko, A.A.
Davydova, V.F.
Tutubalina, E.V.
Ключевые слова : multimodality, multitask, bilinguality, foundation models, FusionBrain challenge
Дата публикации : Фев-2023
Издательство : Самарский национальный исследовательский университет
Библиографическое описание : Bakshandaeva D, Dimitrov D, Arkhipkin V, Shonenkov A, Potanin M, Karachev D, Kuznetsov A, Voronov A, Petiushko A, Davydova V, Tutubalina E. Many heads but one brain: FusionBrain – a single multimodal multitask architecture and a competition. Computer Optics 2023; 47(1): 185-195. DOI: 10.18287/ 2412-6179-CO-1220.
Серия/номер : 47;1
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.
URI (Унифицированный идентификатор ресурса) : 10.18287/2412-6179-CO-1220
http://repo.ssau.ru/handle/Zhurnal-Komputernaya-optika/Many-heads-but-one-brain-FusionBrain-–-a-single-multimodal-multitask-architecture-and-a-competition-102049
Другие идентификаторы : Dspace\SGAU\20230216\102049
Располагается в коллекциях: Журнал "Компьютерная оптика"

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