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Found 4 papers, 2 papers with code
Play the Shannon Game With Language Models: A Human-Free Approach to Summary Evaluation
The goal of a summary is to concisely state the most important information in a document.
Primer AI's Systems for Acronym Identification and Disambiguation
The prevalence of ambiguous acronyms make scientific documents harder to understand for humans and machines alike, presenting a need for models that can automatically identify acronyms in text and disambiguate their meaning.
Sensitivity of BLANC to human-scored qualities of text summaries
We explore the sensitivity of a document summary quality estimator, BLANC, to human assessment of qualities for the same summaries.
Generalized Latent Variable Recovery for Generative Adversarial Networks
The Generator of a Generative Adversarial Network (GAN) is trained to transform latent vectors drawn from a prior distribution into realistic looking photos.
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