CoDA21: Evaluating Language Understanding Capabilities of NLP Models With Context-Definition AlignmentDownload PDF

Anonymous

17 Sept 2021 (modified: 05 May 2023)ACL ARR 2021 September Blind SubmissionReaders: Everyone
Abstract: Pretrained language models (PLMs) have achieved superhuman performance on many benchmarks, creating a need for harder tasks. We introduce CoDA21 (Context Definition Alignment), a challenging benchmark that measures natural language understanding (NLU) capabilities of PLMs: Given a definition and a context each for k words, but not the words themselves, the task is to align the k definitions with the k contexts. CoDA21 requires a deep understanding of contexts and definitions, including complex inference and world knowledge. We find that there is a large gap between human and PLM performance, suggesting that CoDA21 measures an aspect of NLU that is not sufficiently covered in existing benchmarks.
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