SEAL: Segment-wise Extractive-Abstractive Long-form Text Summarization

18 Jun 2020Yao ZhaoMohammad SalehPeter J. Liu

Most prior work in the sequence-to-sequence paradigm focused on datasets with input sequence lengths in the hundreds of tokens due to the computational constraints of common RNN and Transformer architectures. In this paper, we study long-form abstractive text summarization, a sequence-to-sequence setting with input sequence lengths up to 100,000 tokens and output sequence lengths up to 768 tokens... (read more)

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