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In real-world scenarios with naturally occurring datasets, reference summaries are noisy and may contain information that cannot be inferred from the source text.
Attend to medical ontologies: Content selection for clinical abstractive summarization
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PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals
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Comparison of automatic summarisation methods for clinical free text notes
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Can patient record summarization support quality metric abstraction?
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Billion-scale similarity search with gpus
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Newsroom: A dataset of 1.3 million summaries with diverse extractive strategies
Max Grusky, Mor Naaman, and Yoav Artzi. 2018 · 2018
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Publicly available clinical BERT embeddings
Emily Alsentzer, John Murphy, William Boag, Wei-Hung Weng, Di Jindi, Tristan Naumann, and Matthew McDermott. 2019 · 2019
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Hierarchical transformers for multi-document summarization
Evaluating the factual consistency of abstractive text summarization
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Yang Liu and Mirella Lapata. 2019 · 2019
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Ontology-aware clinical abstractive summarization
Sean MacAvaney, Sajad Sotudeh, Arman Cohan, Nazli Goharian, Ish A. Talati, and Ross W. Filice. 2019 · 2019
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Biowordvec, improving biomedical word embeddings with subword information and mesh
Yijia Zhang, Qingyu Chen, Zhihao Yang, Hongfei Lin, and Zhiyong Lu. 2019 · 2019
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Zero-shot clinical acronym expansion via latent meaning cells
Griffin Adams, Mert Ketenci, Shreyas Bhave, Adler Perotte, and Noémie Elhadad. 2020 · 2020
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Intrinsic evaluation of summarization datasets
Rishi Bommasani and Claire Cardie. 2020 · 2020
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Factual error correction for abstractive summarization models
Meng Cao, Yue Dong, Jiapeng Wu, and Jackie Chi Kit Cheung. 2020 · 2020
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Multi-fact correction in abstractive text summarization
Yue Dong, Shuohang Wang, Zhe Gan, Yu Cheng, Jackie Chi Kit Cheung, and Jingjing Liu. 2020 · 2020
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Reducing quantity hallucinations in abstractive summarization
Zheng Zhao, Shay B. Cohen, and Bonnie Webber. 2020 · 2020
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What’s in a summary? laying the groundwork for advances in hospital-course summarization
Griffin Adams, Emily Alsentzer, Mert Ketenci, Jason Zucker, and Noémie Elhadad. 2021 · 2021
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CLIFF: Contrastive learning for improving faithfulness and factuality in abstractive summarization
Shuyang Cao and Lu Wang. 2021 · 2021
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Improving faithfulness in abstractive summarization with contrast candidate generation and selection
Sihao Chen, Fan Zhang, Kazoo Sone, and Dan Roth. 2021 · 2021
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SummEval: Re-evaluating summarization evaluation
Alexander R. Fabbri, Wojciech Kryściński, Bryan McCann, Caiming Xiong, Richard Socher, and Dragomir Radev. 2021 · 2021
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Annotating and modeling fine-grained factuality in summarization
Tanya Goyal and Greg Durrett. 2021 · 2021
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Faisal Ladhak, Esin Durmus, He He, Claire Cardie, and Kathleen McKeown. 2021 · 2021
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Planning with entity chains for abstractive summarization
Shashi Narayan, Yao Zhao, Joshua Maynez, Gonçalo Simoes, and Ryan McDonald. 2021 · 2021
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Scifive: a text-to-text transformer model for biomedical literature
Long N Phan, James T Anibal, Hieu Tran, Shaurya Chanana, Erol Bahadroglu, Alec Peltekian, and Grégoire Altan-Bonnet. 2021 · 2021
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Towards clinical encounter summarization: Learning to compose discharge summaries from prior notes
Han-Chin Shing, Chaitanya Shivade, Nima Pourdamghani, Feng Nan, Philip Resnik, Douglas Oard, and Parminder Bhatia. 2021 · 2021
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Fine-grained factual consistency assessment for abstractive summarization models
Sen Zhang, Jianwei Niu, and Chuyuan Wei. 2021b · 2021
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Detecting hallucinated content in conditional neural sequence generation
Chunting Zhou, Graham Neubig, Jiatao Gu, Mona Diab, Francisco Guzmán, Luke Zettlemoyer, and Marjan Ghazvininejad. 2021 · 2021
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Enhancing factual consistency of abstractive summarization
Chenguang Zhu, William Hinthorn, Ruochen Xu, Qingkai Zeng, Michael Zeng, Xuedong Huang, and Meng Jiang. 2021 · 2021
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