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Language models (LMs) can generate hallucinations and incoherent outputs, which highlights their weak context dependency.
On faithfulness and factuality in abstractive summarization
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Zhilin Yang, Thang Luong, Russ R Salakhutdinov, and Quoc V Le. 2019 · 2019
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Understanding tables with intermediate pre-training
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Datasets: A community library for natural language processing
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Entity-level factual consistency of abstractive text summarization
Feng Nan, Ramesh Nallapati, Zhiguo Wang, Cicero Nogueira dos Santos, Henghui Zhu, Dejiao Zhang, Kathleen McKeown, and Bing Xiang. 2021 · 2021
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Softmax bottleneck makes language models unable to represent multi-mode word distributions
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Revisiting the architectures like pointer networks to efficiently improve the next word distribution, summarization factuality, and beyond
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