Papers › Denoising Distantly Supervised Open-Domain Question Answering

Denoising Distantly Supervised Open-Domain Question Answering

1 Jul 2018ACL 2018 7archive 2025-07-28

Yankai Lin, Haozhe Ji, Zhiyuan Liu, Maosong Sun

Distantly supervised open-domain question answering (DS-QA) aims to find answers in collections of unlabeled text. Existing DS-QA models usually retrieve related paragraphs from a large-scale corpus and apply reading comprehension technique to extract answers from the most relevant paragraph. They ignore the rich information contained in other paragraphs. Moreover, distant supervision data inevitably accompanies with the wrong labeling problem, and these noisy data will substantially degrade the performance of DS-QA. To address these issues, we propose a novel DS-QA model which employs a paragraph selector to filter out those noisy paragraphs and a paragraph reader to extract the correct answer from those denoised paragraphs. Experimental results on real-world datasets show that our model can capture useful information from noisy data and achieve significant improvements on DS-QA as compared to all baselines.

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thunlp/OpenQA officialmentioned in paperpytorchMIT report

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Tasks

DenoisingInformation RetrievalOpen-Domain Question AnsweringQuestion AnsweringReading Comprehension

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Open-Domain Question Answering Quasar Denoising QA EM (Quasar-T) 42.2 #2 of 6 Archive leaderboard report
Open-Domain Question Answering Quasar Denoising QA F1 (Quasar-T) 49.3 #2 of 6 Archive leaderboard report
Open-Domain Question Answering SearchQA Denoising QA EM 58.8 #6 of 14 Archive leaderboard report
Open-Domain Question Answering SearchQA Denoising QA F1 64.5 #6 of 14 Archive leaderboard report
Open-Domain Question Answering SearchQA Denoising QA N-gram F1 - #6 of 14 Archive leaderboard report
Open-Domain Question Answering SearchQA Denoising QA Unigram Acc - #6 of 14 Archive leaderboard report
Question Answering Quasart-T Denoising QA EM 42.2 #5 of 7 Archive leaderboard report

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