Papers by Antonio Jimeno Yepes

4 papers
M3: Multi-level dataset for Multi-document summarisation of Medical studies (2022.findings-emnlp)

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Challenge: Existing summarisation systems are not up to such complex tasks, yet limited tools exist to determine where and why they are failing.
Approach: They propose to use a dataset to evaluate the quality of summarisation systems in the biomedical domain.
Outcome: The proposed model can be used to evaluate the quality of summarisation systems in the biomedical domain.
Grey-box Adversarial Attack And Defence For Sentiment Classification (2021.naacl-main)

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Challenge: Recent advances in deep neural networks have created applications for a range of different domains.
Approach: They propose a grey-box adversarial attack and defence framework for sentiment classification . they show that the framework produces an improved classifier that is robust in defending .
Outcome: The proposed framework produces an improved classifier that is robust in defending against multiple adversarial attacking methods.
MEDLINE as a Parallel Corpus: a Survey to Gain Insight on French-, Spanish- and Portuguese-speaking Authors’ Abstract Writing Practice (2020.lrec-1)

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Challenge: Existing corpora are used to train and evaluate machine translation systems, but little information is available about the methods used for producing the corpus, including translation direction.
Approach: They used PubMed and publisher websites to obtain contact information for MEDLINE authors and asked about their abstract writing practices.
Outcome: The authors of MEDLINE articles included in the English/Spanish, English/FR, and English/Portuguese (EN/PT) WMT 2019 test sets reported a response rate of over 20% .
Parallel Corpora for the Biomedical Domain (L18-1)

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Challenge: Existing corpora of parallel corporata are being used in the biomedical domain . MT is known to support readers' access to textual documents in a language other than their native language .
Approach: They propose to leverage parallel corpora to implement cross-lingual information retrieval or machine translation tools.
Outcome: The proposed corpus is being used in the biomedical task at the conference on machine translation (WMT'16 and WMT'17) it can be leveraged to provide access to health information in languages other than English.

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