Adversarial Examples for Evaluating Reading Comprehension Systems

EMNLP 2017 Robin JiaPercy Liang

Standard accuracy metrics indicate that reading comprehension systems are making rapid progress, but the extent to which these systems truly understand language remains unclear. To reward systems with real language understanding abilities, we propose an adversarial evaluation scheme for the Stanford Question Answering Dataset (SQuAD)... (read more)

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