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Found 4 papers, 1 papers with code
COIN – an Inexpensive and Strong Baseline for Predicting Out of Vocabulary Word Embeddings
Word embedding models only include terms that occur a sufficient number of times in their training corpora.
Beyond Labels: Empowering Human Annotators with Natural Language Explanations through a Novel Active-Learning Architecture
Our AL architecture leverages an explanation-generation model to produce explanations guided by human explanations, a prediction model that utilizes generated explanations toward prediction faithfully, and a novel data diversity-based AL sampling strategy that benefits from the explanation annotations.
Cannot Predict Comment Volume of a News Article before (a few) Users Read It
We show that the early arrival rate of comments is the best indicator of the eventual number of comments.
Regular Expression Guided Entity Mention Mining from Noisy Web Data
Finally, a human expert is asked to label a small set of documents and the neural network is fine tuned on those documents.
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