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Many Heads but One Brain: Fusion Brain -- a Competition and a Single Multimodal Multitask Architecture

arXiv 2111.10974 ↗First posted 22 Nov 2021cs.CV cs.AI cs.CLcited by 0

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Abstract (arXiv)

Supporting the current trend in the AI community, we present the AI Journey 2021 Challenge called Fusion Brain, the first competition which is targeted to make the universal architecture which could process different modalities (in this case, images, texts, and code) and solve multiple tasks for vision and language. The Fusion Brain 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 center 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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 39 of its 57 references that are in the map. First posted on arXiv 22 Nov 2021.

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References · 39

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  4. 2020Language Models are Few-Shot Learnerscited by 32,199
  5. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  6. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
  7. 2021Zero-Shot Text-to-Image Generationcited by 4,276
  8. 2019Parameter-Efficient Transfer Learning for NLPcited by 4,195
  9. 2021On the Opportunities and Risks of Foundation Modelscited by 3,961
  10. 2016Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotationscited by 2,646
  11. 2016Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answeringcited by 2,498
  12. 2019VisualBERT: A Simple and Performant Baseline for Vision and Languagecited by 1,291
27 more
  1. 2021Perceiver: General Perception with Iterative Attentioncited by 1,089
  2. 2021Open-vocabulary Object Detection via Vision and Language Knowledge Distillationcited by 903
  3. 2021MDETR -- Modulated Detection for End-to-End Multi-Modal Understandingcited by 811
  4. 2020AdapterFusion: Non-Destructive Task Composition for Transfer Learningcited by 780
  5. 2021Perceiver IO: A General Architecture for Structured Inputs & Outputscited by 616
  6. 2021Carbon Emissions and Large Neural Network Trainingcited by 561
  7. 2019Quantifying the Carbon Emissions of Machine Learningcited by 516
  8. 2020CodeBLEU: a Method for Automatic Evaluation of Code Synthesiscited by 468
  9. 2020Multi-modal Transformer for Video Retrievalcited by 395
  10. 2021Unified Pre-training for Program Understanding and Generationcited by 361
  11. 2021Attention Bottlenecks for Multimodal Fusioncited by 361
  12. 2019Multi-Task Deep Neural Networks for Natural Language Understandingcited by 349
  13. 2020Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learningcited by 246
  14. 2015YFCC100M: The New Data in Multimedia Researchcited by 234
  15. 2021CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Taskscited by 199
  16. 2021UniT: Multimodal Multitask Learning with a Unified Transformercited by 195
  17. 2021Pretrained Transformers as Universal Computation Enginescited by 162
  18. 2021MDMMT: Multidomain Multimodal Transformer for Video Retrievalcited by 78
  19. 2021AVATAR: A Parallel Corpus for Java-Python Program Translationcited by 59
  20. 2019Evaluating Sequence-to-Sequence Models for Handwritten Text Recognitioncited by 58
  21. 2020Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less Datacited by 50
  22. 2021Multi-task Retrieval for Knowledge-Intensive Taskscited by 44
  23. 2018Multimodal Language Analysis with Recurrent Multistage Fusioncited by 43
  24. 2020Detecting Hate Speech in Multi-modal Memescited by 38
  25. 2019No Padding Please: Efficient Neural Handwriting Recognitioncited by 5
  26. 2020Mutual Modality Learning for Video Action Classificationcited by 3
  27. 2021StackMix and Blot Augmentations for Handwritten Text Recognitioncited by 2

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