Your Daily AI Research tl;dr - 2022-08-24 ??

Welcome to your official daily AI research tl;dr (often with code and news) for AI professionals where I share the most exciting papers I find daily, along with a one-liner summary to help you quickly determine if the article (and code) is worth investigating.

1?? Z-Code++: A Pre-trained Language Model Optimized for Abstractive Summarization?

As the title says, Z-code++ is "a new pre-trained language model optimized for abstractive text summarization."

Wonder what is abstractive text summarization?

"Abstractive summarizers paraphrase the idea of the source documents in a new form, and have a potential of generating more concise and coherent summaries."

Link to the paper: https://arxiv.org/pdf/2208.09770.pdf

2?? Image as a Foreign Language: BEIT Pretraining for All Vision and Vision-Language Tasks

"A general-purpose multimodal foundation model BEIT-3, which achieves state-of-the-art transfer performance on both vision and vision-language tasks."

Link to the paper: https://arxiv.org/pdf/2208.10442.pdf

Code: https://github.com/microsoft/unilm/tree/master/beit

Join the discussion with fellow AI professionals on Discord!

?? "Google research AI image noise reduction is out of this world"

Google recently release MultiNeRF: A code for Mip-NeRF 360, Ref-NeRF, and RawNeRF.

"The algorithms run on raw image data and adds AI magic to figure out what footage 'should have' looked like without the distinct video noise generated by imaging sensors."

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Thank you for reading,

Louis