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Learning to Generate Questions with Adaptive Copying Neural Networks

Summary: Adaptive copying seq2seq QG with biLSTM encoder, global attention, and a copying decoder for questions from sentences/paragraphs. Outperforms SOTA on BLEU/ROUGE, enabling scalable QA data generation and QA-driven data-management benchmarks. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5631
Venue
SIGMOD
Year
2019
Pagerank
4.3079067e-05
Overall Rank
9,667 | 32.75%
DOI
10.1145/3299869.3300100

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8,346 Deep Learning: Systems and Responsibility 2021 SIGMOD 4.5420668e-05
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