DARPA's Sarcasm Detector Totes Gets Your Drift: Science Fiction in the News

As they explain in a study published in the journal, Entropy, Garibay and UCF PhD student Ramya Akula have built --an interpretable deep learning model using multi-head self-attention and gated recurrent units. The multi-head self-attention module aids in identifying crucial sarcastic cue-words from the input, and the recurrent units learn long-range dependencies between these cue-words to better classify the input text.--