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1
The statistical advantage of automatic NLG metrics at the system level ...
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2
Evaluation Examples are not Equally Informative: How should that change NLP Leaderboards? ...
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3
Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation ...
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4
The statistical advantage of automatic NLG metrics at the system level ...
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5
Swords: A Benchmark for Lexical Substitution with Improved Data Coverage and Quality ...
Lee, Mina; Donahue, Chris; Jia, Robin. - : arXiv, 2021
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Swords: A Benchmark for Lexical Substitution with Improved Data Coverage and Quality ...
Abstract: Read the paper on the folowing link: https://www.aclweb.org/anthology/2021.naacl-main.345/ Abstract: We release a new benchmark for lexical substitution, the task of finding appropriate substitutes for a target word in a context. For writing, lexical substitution systems can assist humans by suggesting words that humans cannot easily think of. However, existing benchmarks depend on human recall as the only source of data, and therefore lack coverage of the substitutes that would be most helpful to humans. Furthermore, annotators often provide substitutes of low quality, which are not actually appropriate in the given context. We collect higher-coverage and higher-quality data by framing lexical substitution as a classification problem, guided by the intuition that it is easier for humans to judge the appropriateness of candidate substitutes than conjure them from memory. To this end, we use a context-free thesaurus to produce candidates and rely on human judgement to determine contextual appropriateness. ...
Keyword: Artificial Intelligence; Computer Science and Engineering; Intelligent System; Natural Language Processing
URL: https://dx.doi.org/10.48448/xrvg-6t89
https://underline.io/lecture/19653-swords-a-benchmark-for-lexical-substitution-with-improved-data-coverage-and-quality
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7
Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little ...
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