2023
DOI: 10.1609/aaai.v37i8.26143
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GLUECons: A Generic Benchmark for Learning under Constraints

Abstract: Recent research has shown that integrating domain knowledge into deep learning architectures is effective; It helps reduce the amount of required data, improves the accuracy of the models' decisions, and improves the interpretability of models. However, the research community lacks a convened benchmark for systematically evaluating knowledge integration methods. In this work, we create a benchmark that is a collection of nine tasks in the domains of natural language processing and computer vision. In all cases… Show more

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