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Machine Reading Comprehension/Ushahidi
Rekodi ya ushahidi wa mbinu

Machine Reading Comprehension

Machine reading comprehension (MRC), popularised by the SQuAD benchmark of Rajpurkar, Zhang, Lopyrev and Liang (2016), is a natural-language-processing task in which a model reads a given passage and answers multiple-choice or open-ended questions about it. It turns a passage plus a question into a machine-generated answer, supporting information retrieval, educational technology, and querying research databases.

Sources recorded, not reviewed

Rekodi ya chanzo

Nukuu zimehamishwa kwa uhalisi kutoka kwa rekodi ya chanzo cha mbinu. Hakuna uthibitisho wa kiwango cha dai unaodokezwa kutoka kwao.

Neural Machine Reading Comprehension (MRC)
Rekodi ya mbinu ya kiajenda · process-pipeline / text-mining
  • Rajpurkar, P., Zhang, J., Lopyrev, K. & Liang, P. (2016). SQuAD: 100,000+ Questions for Machine Comprehension of Text. EMNLP, 2383-2392. · DOI 10.18653/v1/D16-1264
  • Yang, Z. et al. (2018). HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering. EMNLP. · DOI 10.18653/v1/D18-1259
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Same method familyDomain Adaptationmachine-suggested · Relational suggestion, not evidence.Same method familySentiment Analysismachine-suggested · Relational suggestion, not evidence.Same method familyText Classificationmachine-suggested · Relational suggestion, not evidence.

Hali ya ushahidi

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Vyanzo

2 nukuu zilizorekodiwa, ziliyonakiliwa kutoka kwa rekodi ya chanzo cha mbinu.

Vitendo

Fungua ukurasa wa mbinu
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