Hot papers on arXiv from the past month – July 2020

AIHub 

Here are the most tweeted papers that were uploaded onto arXiv during July 2020. Results are powered by Arxiv Sanity Preserver. Abstract: Massive language models are the core of modern NLP modeling and have been shown to encode impressive amounts of commonsense and factual information. However, that knowledge exists only within the latent parameters of the model, inaccessible to inspection and interpretation, and even worse, factual information memorized from the training corpora is likely to become stale as the world changes. Knowledge stored as parameters will also inevitably exhibit all of the biases inherent in the source materials.

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