no code implementations • RANLP 2021 • Jingyi You, Chenlong Hu, Hidetaka Kamigaito, Hiroya Takamura, Manabu Okumura
Neural sequence-to-sequence (Seq2Seq) models and BERT have achieved substantial improvements in abstractive document summarization (ADS) without and with pre-training, respectively.
no code implementations • COLING 2022 • Dongyuan Li, Jingyi You, Kotaro Funakoshi, Manabu Okumura
Text infilling aims to restore incomplete texts by filling in blanks, which has attracted more attention recently because of its wide application in ancient text restoration and text rewriting.
no code implementations • COLING 2022 • Jingyi You, Dongyuan Li, Manabu Okumura, Kenji Suzuki
Automated radiology report generation aims to generate paragraphs that describe fine-grained visual differences among cases, especially those between the normal and the diseased.
no code implementations • NAACL 2022 • Jingyi You, Dongyuan Li, Hidetaka Kamigaito, Kotaro Funakoshi, Manabu Okumura
Previous studies on the timeline summarization (TLS) task ignored the information interaction between sentences and dates, and adopted pre-defined unlearnable representations for them.