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Pre-trained language models (PLMs) fail to generate long-form narrative text because they do not consider global structure.
Towards few-shot fact-checking via perplexity
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Nayeon Lee, Belinda Z. Li, Sinong Wang, Wen-tau Yih, Hao Ma, and Madian Khabsa. 2020 · 2020
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BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
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Do massively pretrained language models make better storytellers?
Abigail See, Aneesh Pappu, Rohun Saxena, Akhila Yerukola, and Christopher D. Manning. 2019 · 2019
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MEGATRON-CNTRL: Controllable story generation with external knowledge using large-scale language models
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Towards generating long and coherent text with multi-level latent variable models
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