Fetching the paper…
Reading the bibliography…
We consider the problem of automatically generating a narrative biomedical evidence summary from multiple trial reports.
HuggingFace’s Transformers: State-of-the-art Natural Language Processing
Wolf T, Debut L, Sanh V, Chaumond J, Delangue C, Moi A, et al · 1910
Earlier work this paper cites.
Evidence-based medicine
Sackett DL · 1997
Earlier work this paper cites.
Advances in automatic text summarization
Maybury M · 1999
Earlier work this paper cites.
ROUGE: A package for automatic evaluation of summaries
Lin CY · 2004
Earlier work this paper cites.
Answer extraction, semantic clustering, and extractive summarization for clinical question answering
Demner-Fushman D, Lin J · 2006
Earlier work this paper cites.
Neural text summarization: A critical evaluation
Kryściński W, Keskar NS, McCann B, Xiong C, Socher R · 2008
Earlier work this paper cites.
An Investigation into the Validity of Some Metrics for Automatically Evaluating Natural Language Generation Systems
Reiter E, Belz A · 2009
Earlier work this paper cites.
A corpus for evidence based medicine summarisation
Mollá D · 2010
Earlier work this paper cites.
Inhaled antibiotics for long-term therapy in cystic fibrosis
Ryan G, Singh M, Dwan K · 2011
Earlier work this paper cites.
AskHERMES: An online question answering system for complex clinical questions
Cao Y, Liu F, Simpson P, Antieau L, Bennett A, Cimino JJ, et al · 2011
Earlier work this paper cites.
Automatic summarization
Nenkova A, McKeown K · 2011
Earlier work this paper cites.
Sequence to sequence learning with neural networks
Sutskever I, Vinyals O, Le QV · 2014
Earlier work this paper cites.
A neural attention model for abstractive sentence summarization
Rush AM, Chopra S, Weston J · 2015
Earlier work this paper cites.
Aligning books and movies: Towards story-like visual explanations by watching movies and reading books
Zhu Y, Kiros R, Zemel R, Salakhutdinov R, Urtasun R, Torralba A, et al · 2015
Earlier work this paper cites.
A corpus for research in text processing for evidence based medicine
Mollá D, Santiago-Martínez ME, Sarker A, Paris C · 2016
Cited alongside, same era.
RobotReviewer: evaluation of a system for automatically assessing bias in clinical trials
Marshall IJ, Kuiper J, Wallace BC · 2016
Cited alongside, same era.
An introduction to systematic reviews
Gough D, Oliver S, Thomas J · 2017
Cited alongside, same era.
Automated text summarisation and evidence-based medicine: A survey of two domains; 2017.
Sarker A, Molla D, Paris C · 2017
Cited alongside, same era.
Get to the point: Summarization with pointer-generator networks
See A, Liu PJ, Manning CD · 2017
Cited alongside, same era.
Attention is all you need
Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, et al · 2017
Cited alongside, same era.
Results of the Seventh Edition of the BioASQ Challenge
Nentidis A, Bougiatiotis K, Krithara A, Paliouras G · 2019
Later among the works it cites.
BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Lewis M, Liu Y, Goyal N, Ghazvininejad M, Mohamed A, Levy O, et al · 2019
Later among the works it cites.
Pegasus: Pre-training with extracted gap-sentences for abstractive summarization
Zhang J, Zhao Y, Saleh M, Liu PJ · 2019
Later among the works it cites.
Abstractive summarization: A survey of the state of the art
Lin H, Ng V · 2019
Later among the works it cites.
Best practices for the human evaluation of automatically generated text
Van Der Lee C, Gatt A, Van Miltenburg E, Wubben S, Krahmer E · 2019
Later among the works it cites.
Roberta: A robustly optimized bert pretraining approach
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Automating biomedical evidence synthesis: RobotReviewer
Marshall IJ, Kuiper J, Banner E, Wallace BC · 2017
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Devlin J, Chang MW, Lee K, Toutanova K · 2018
Cited alongside, same era.
A simple method for commonsense reasoning
Trinh TH, Le QV · 2018
Cited alongside, same era.
Don’t give me the details, just the summary! topic-aware convolutional neural networks for extreme summarization
Narayan S, Cohen SB, Lapata M · 2018
Cited alongside, same era.
Machine learning for identifying randomized controlled trials: an evaluation and practitioner’s guide
Marshall IJ, Noel-Storr A, Kuiper J, Thomas J, Wallace BC · 2018
Cited alongside, same era.
A corpus with multi-level annotations of patients, interventions and outcomes to support language processing for medical literature
Nye B, Li JJ, Patel R, Yang Y, Marshall IJ, Nenkova A, et al · 2018
Cited alongside, same era.
Liu Y, Ott M, Goyal N, Du J, Joshi M, Chen D, et al · 2019
Later among the works it cites.
Inferring which medical treatments work from reports of clinical trials
Lehman E, DeYoung J, Barzilay R, Wallace BC · 2019
Later among the works it cites.
Available from: https://ehudreiter.com/2020/04/27/accuracy-errors-go-beyond-getting-facts-wrong/
Reiter E. Accuracy Errors Go Beyond Getting Facts Wrong; 2020 · 2020
Closest in time.
On Faithfulness and Factuality in Abstractive Summarization
Maynez J, Narayan S, Bohnet B, McDonald R · 2020
Closest in time.
Asking and answering questions to evaluate the factual consistency of summaries
Wang A, Cho K, Lewis M · 2020
Closest in time.
Fact-based Content Weighting for Evaluating Abstractive Summarisation
Xu X, Dušek O, Li J, Rieser V, Konstas I · 2020
Closest in time.
Don’t Stop Pretraining: Adapt Language Models to Domains and Tasks
Gururangan S, Marasović A, Swayamdipta S, Lo K, Beltagy I, Downey D, et al · 2020
Closest in time.
Evidence Inference 2.0: More Data, Better Models
DeYoung J, Lehman E, Nye B, Marshall IJ, Wallace BC · 2020
Closest in time.