understanding-ai
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flrngel
personal repository
get doc -> ocr -> summary each page -> final summary from all pages
# Summary All-Seeing 1B (AS-1B) dataset: we propose a new large-scale dataset (AS-1B) for open-world panoptic visual recognition and understanding, using an economical semi-automatic data engine that combines the power...
Repository for sarcasm. Not a real deep vector DB (just a python code). Related Post: - https://www.linkedin.com/posts/dhruv-anand-ainorthstartech_ainorthstartech-vectorsearch-vectordatabases-activity-7053961131685490688-_UFB?utm_source=share&utm_medium=member_desktop
Summary - uses blip/blip2 to generate a simple caption - uses grit/detectron2 to generate a dense caption - uses segment anything to generate a region_semantic information - unify all above...
https://arxiv.org/abs/1807.03748 ~big fan of Aaron van den Oord~ # Abstract - propose universal unsupervised learning approach to extract useful representations from high-dimensional data, **CPC(Contrastive Predictive Coding)** - use probabilistic contrastive...
https://arxiv.org/abs/1901.03909 This follows [ Adding One Neuron Can Eliminate All Bad Local Minima](https://arxiv.org/abs/1805.08671) and [Elimination of All Bad Local Minima in Deep Learning](https://arxiv.org/abs/1901.00279) # Key point   ***a*** and...
https://arxiv.org/pdf/1704.04861.pdf # Summary    
http://arxiv.org/abs/1812.10464 # Notes - Model learn joint multilingual sentence representations  ## Pre-training techniques using Moses tools - punctuation normalization - non printing chars removal - Tokenization ## Paper summary...
https://arxiv.org/pdf/1901.00884v1.pdf   # 4. Conclusion 1. It is easy to construct examples where the intermediate representations have no match, even when the outputs of the network are identical. 2....
https://arxiv.org/abs/1711.00937 # Abstract - paper proposes model(**VQ-VAE**) that learns "discrete representations" - differs from VAEs - encode network outputs discrete (means not continuous) - prior learnt than static - circumvent...