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Open Graph

title

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2026-02-23 12:24:08

raw text

Beat the AI: Investigating Adversarial Human Annotation for Reading Comprehension AdversarialQA Home Data Leaderboard UCL NLP  AdversarialQA Datasets produced in Beat the AI: Investigating Adversarial Human Annotation for Reading Comprehension TACL Paper Dataset Download Dataset Distribution under CC BY-SA 3.0 Authors: Max Bartolo , Alastair Roberts , Johannes Welbl , Sebastian Riedel , Pontus Stenetorp Three New RC Datasets We have created three new Reading Comprehension datasets constructed using an adversarial model-in-the-loop. We use three different models; BiDAF ( Seo et al., 2016 ), BERT Large ( Devlin et al., 2018 ), and RoBERTa Large ( Liu et al., 2019 ) in the annotation loop and construct three datasets; D(BiDAF) , D(BERT) , and D(RoBERTa) , each with 10,000 training examples, 1,000 validation, and 1,000 test examples. ...

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