Augmenting Transformers for Open Domain Procedural Text Comprehesion
Recent advances in deep learning model architectures have permitted state-of-the-art results in various fields such as NLP and CV. Although these systems have matched and, in some cases, surpassed human performance, many of them are still treated as black boxes, with sometimes unpredictable results....
Main Author: | Pei, Yixuan |
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Other Authors: | Shrobe, Howard |
Format: | Thesis |
Published: |
Massachusetts Institute of Technology
2022
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Online Access: | https://hdl.handle.net/1721.1/139980 |
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