📜SimVLM explained. What the authors tell us, what they don’t tell us and how this all works. Enjoy with coffee!
📺 Vision & Language Transformer explained (ViLBERT): https://youtu.be/dd7nE4nbxN0
📺 ViT explained: https://youtu.be/DVoHvmww2lQ
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Paper:
📜 Wang, Zirui, Jiahui Yu, Adams Wei Yu, Zihang Dai, Yulia Tsvetkov, and Yuan Cao. "SimVLM: Simple Visual Language Model Pretraining with Weak Supervision." arXiv preprint arXiv:2108.10904 (2021). https://arxiv.org/abs/2108.10904
🔗 SimVLM AI Google Blog post: https://ai.googleblog.com/2021/10/simvlm-simple-visual-language-model-pre.html
📜 Jia, Chao, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc V. Le, Yunhsuan Sung, Zhen Li, and Tom Duerig. "Scaling up visual and vision-language representation learning with noisy text supervision." arXiv preprint arXiv:2102.05918 (2021). https://arxiv.org/abs/2102.05918
📜GPT-3 paper: Brown, Tom B., Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan et al. "Language models are few-shot learners." arXiv preprint arXiv:2005.14165 (2020). https://arxiv.org/abs/2005.14165
📺 GPT-3 video: https://youtu.be/5fqxPOaaqi0
Outline:
00:00 SimVLM
01:15 End-to-end image processing
03:01 Objective: Prefix Language Modelling
06:38 The secret ingredient
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