🔗 Who cites «Addressing Semantic Drift in Question Generation for Semi-Supervised Question Answering»

69 papers of our library cite it (of the 141,840 whose bibliographies we read) · 6 with a page here, the most cited first · ← back to «Addressing Semantic Drift in Question Generation for Semi-Supervised Question Answering»

1. Unified Language Model Pre-training for Natural Language Understanding and GenerationarXiv:1905.03197Li Dong, Nan Yang, Wenhui Wang, et al.2019 · 1,406 citations
   ProphetNet: Predicting Future N-gram for Sequence-to-SequencePre-trainingFindings of the Association for Computational LinguisticsWeizhen Qi, Yu Yan, Yeyun Gong, et al.2020 · 453 citations
2. UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-TrainingarXiv:2002.12804Hangbo Bao, Li Dong, Furu Wei, et al.2020 · 384 citations
   An Empirical Survey of Data Augmentation for Limited Data Learning in NLPTransactions of the Association for Computational Linguistics (TACL)Jiaao Chen, Derek Tam, Colin Raffel, et al.2023 · 253 citations
   Evaluating Factuality in Generation with Dependency-level EntailmentFindings of the Association for Computational LinguisticsTanya Goyal, Greg Durrett2020 · 203 citations
   ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language GenerationInternational Joint Conference on Artificial IntelligenceDongling Xiao, Han Zhang, Yukun Li, et al.2020 · 163 citations

63 more papers of our library cite it; they have no page here yet.

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