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A Large-Scale Multi-Length Headline Corpus for Analyzing Length-Constrained Headline Generation Model Evaluation
Yuta Hitomi
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Yuya Taguchi
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Hideaki Tamori
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Ko Kikuta
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Jiro Nishitoba
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Naoaki Okazaki
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Kentaro Inui
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Manabu Okumura
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Paper Details:
Month: October–November
Year: 2019
Location: Tokyo, Japan
Venue:
INLG |
WS |
SIG: SIGGEN
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https://duc.nist.gov/duc2004/
https://cl.asahi.com/api_data/
https://github.com/facebookarchive/
https://github.com/asahi-research/Gingo
https://github.com/google/
https://github.com/OpenNMT/OpenNMT-py
https://github.com/pytorch/fairseq
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