This paper introduces PeKo, a crowd-sourced annotation of preconditions between event pairs in newswire, an order of magnitude larger than prior text annotations.
Predicting how events induce emotions in the characters of a story is typically seen as a standard multi-label classification task, which usually treats labels as anonymous classes to predict.
Ranked #1 on Emotion Classification on ROCStories
A SLDS is a dynamical system in which the latent dynamics of the system (i. e. how the state vector transforms over time) is controlled by top-level discrete switching variables.
We introduce Multee, a general architecture that can effectively use entailment models for multi-hop QA tasks.
We automatically generate fake sentences by corrupting original sentences from a source collection and train the encoders to produce representations that are effective at detecting fake sentences.