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‎content/publication/neves-etal-2024-findings/cite.bib‎

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@inproceedings{neves-etal-2024-findings,
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title = "Findings of the {WMT} 2024 Biomedical Translation Shared Task: Test Sets on Abstract Level",
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author = "Neves, Mariana and
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Grozea, Cristian and
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Thomas, Philippe and
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Roller, Roland and
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Bawden, Rachel and
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N{\'e}v{\'e}ol, Aur{\'e}lie and
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Castle, Steffen and
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Bonato, Vanessa and
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Di Nunzio, Giorgio Maria and
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Vezzani, Federica and
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Vicente Navarro, Maika and
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Yeganova, Lana and
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Jimeno Yepes, Antonio",
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editor = "Haddow, Barry and
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Kocmi, Tom and
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Koehn, Philipp and
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Monz, Christof",
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booktitle = "Proceedings of the Ninth Conference on Machine Translation",
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month = nov,
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year = "2024",
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address = "Miami, Florida, USA",
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publisher = "Association for Computational Linguistics",
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url = "https://aclanthology.org/2024.wmt-1.6/",
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doi = "10.18653/v1/2024.wmt-1.6",
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pages = "124--138",
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abstract = "We present the results of the ninth edition of the Biomedical Translation Task at WMT{'}24. We released test sets for six language pairs, namely, French, German, Italian, Portuguese, Russian, and Spanish, from and into English. Eachtest set consists of 50 abstracts from PubMed. Differently from previous years, we did not split abstracts into sentences. We received submissions from five teams, and for almost all language directions. We used a baseline/comparison system based on Llama 3.1 and share the source code at https://github.com/cgrozea/wmt24biomed-ref."
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}

‎content/publication/neves-etal-2024-findings/index.md‎

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---
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# Documentation: https://wowchemy.com/docs/managing-content/
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title: "Findings of the WMT 2024 Biomedical Translation Shared Task: Test Sets on Abstract Level"
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authors: ["Mariana Neves", "Cristian Grozea", "Philippe Thomas", "Roland Roller", "Rachel Bawden", "Aurélie Névéol", "Steffen Castle", "Vanessa Bonato", "Giorgio Maria Di Nunzio", "Federica Vezzani", "Maika Vicente Navarro", "Lana Yeganova", "Antonio Jimeno Yepes"]
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date: 2024-11-01
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doi: ""
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# Schedule page publish date (NOT publication's date).
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publishDate: 2024-11-01
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# Publication type.
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# Legend: 0 = Uncategorized; 1 = Conference paper; 2 = Journal article;
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# 3 = Preprint / Working Paper; 4 = Report; 5 = Book; 6 = Book section;
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# 7 = Thesis; 8 = Patent
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publication_types: ["1"]
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# Publication name and optional abbreviated publication name.
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publication: "Proceedings of the Ninth Conference on Machine Translation"
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publication_short: "WMT 2024"
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abstract: "We present the results of the ninth edition of the Biomedical Translation Task at WMT’24. We released test sets for six language pairs, namely, French, German, Italian, Portuguese, Russian, and Spanish, from and into English. Eachtest set consists of 50 abstracts from PubMed. Differently from previous years, we did not split abstracts into sentences. We received submissions from five teams, and for almost all language directions. We used a baseline/comparison system based on Llama 3.1 and share the source code at https://github.com/cgrozea/wmt24biomed-ref."
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# Summary. An optional shortened abstract.
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summary: ""
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tags: []
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categories: []
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featured: false
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# Custom links (optional).
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# Uncomment and edit lines below to show custom links.
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# links:
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# - name: Follow
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# url: https://twitter.com
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# icon_pack: fab
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# icon: twitter
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url_pdf: "https://aclanthology.org/2024.wmt-1.6.pdf"
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url_code:
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url_dataset:
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url_poster:
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url_project:
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url_slides:
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url_source:
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url_video:
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# Featured image
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# To use, add an image named `featured.jpg/png` to your page's folder.
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# Focal points: Smart, Center, TopLeft, Top, TopRight, Left, Right, BottomLeft, Bottom, BottomRight.
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image:
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caption: ""
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focal_point: ""
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preview_only: false
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# Associated Projects (optional).
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# Associate this publication with one or more of your projects.
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# Simply enter your project's folder or file name without extension.
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# E.g. `internal-project` references `content/project/internal-project/index.md`.
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# Otherwise, set `projects: []`.
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projects: []
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# Slides (optional).
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# Associate this publication with Markdown slides.
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# Simply enter your slide deck's filename without extension.
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# E.g. `slides: "example"` references `content/slides/example/index.md`.
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# Otherwise, set `slides: ""`.
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slides: ""
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---

‎content/publication/raithel-etal-2024-dataset/cite.bib‎

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@inproceedings{raithel-etal-2024-dataset,
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title = "A Dataset for Pharmacovigilance in {G}erman, {F}rench, and {J}apanese: Annotating Adverse Drug Reactions across Languages",
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author = {Raithel, Lisa and
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Yeh, Hui-Syuan and
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Yada, Shuntaro and
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Grouin, Cyril and
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Lavergne, Thomas and
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N{\'e}v{\'e}ol, Aur{\'e}lie and
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Paroubek, Patrick and
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Thomas, Philippe and
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Nishiyama, Tomohiro and
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M{\"o}ller, Sebastian and
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Aramaki, Eiji and
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Matsumoto, Yuji and
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Roller, Roland and
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Zweigenbaum, Pierre},
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editor = "Calzolari, Nicoletta and
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Kan, Min-Yen and
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Hoste, Veronique and
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Lenci, Alessandro and
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Sakti, Sakriani and
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Xue, Nianwen",
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booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
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month = may,
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year = "2024",
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address = "Torino, Italia",
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publisher = "ELRA and ICCL",
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url = "https://aclanthology.org/2024.lrec-main.36/",
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pages = "395--414",
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abstract = "User-generated data sources have gained significance in uncovering Adverse Drug Reactions (ADRs), with an increasing number of discussions occurring in the digital world. However, the existing clinical corpora predominantly revolve around scientific articles in English. This work presents a multilingual corpus of texts concerning ADRs gathered from diverse sources, including patient fora, social media, and clinical reports in German, French, and Japanese. Our corpus contains annotations covering 12 entity types, four attribute types, and 13 relation types. It contributes to the development of real-world multilingual language models for healthcare. We provide statistics to highlight certain challenges associated with the corpus and conduct preliminary experiments resulting in strong baselines for extracting entities and relations between these entities, both within and across languages."
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}

‎content/publication/raithel-etal-2024-dataset/index.md‎

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---
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# Documentation: https://wowchemy.com/docs/managing-content/
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title: "A Dataset for Pharmacovigilance in German, French, and Japanese: Annotating Adverse Drug Reactions across Languages"
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authors: ["Lisa Raithel", "Hui-Syuan Yeh", "Shuntaro Yada", "Cyril Grouin", "Thomas Lavergne", "Aurélie Névéol", "Patrick Paroubek", "Philippe Thomas", "Tomohiro Nishiyama", "Sebastian Möller", "Eiji Aramaki", "Yuji Matsumoto", "Roland Roller", "Pierre Zweigenbaum"]
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date: 2024-05-01
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doi: ""
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# Schedule page publish date (NOT publication's date).
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publishDate: 2024-05-01
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# Publication type.
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# Legend: 0 = Uncategorized; 1 = Conference paper; 2 = Journal article;
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# 3 = Preprint / Working Paper; 4 = Report; 5 = Book; 6 = Book section;
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# 7 = Thesis; 8 = Patent
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publication_types: ["1"]
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# Publication name and optional abbreviated publication name.
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publication: "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)"
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publication_short: "LREC-COLING 2024"
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abstract: "User-generated data sources have gained significance in uncovering Adverse Drug Reactions (ADRs), with an increasing number of discussions occurring in the digital world. However, the existing clinical corpora predominantly revolve around scientific articles in English. This work presents a multilingual corpus of texts concerning ADRs gathered from diverse sources, including patient fora, social media, and clinical reports in German, French, and Japanese. Our corpus contains annotations covering 12 entity types, four attribute types, and 13 relation types. It contributes to the development of real-world multilingual language models for healthcare. We provide statistics to highlight certain challenges associated with the corpus and conduct preliminary experiments resulting in strong baselines for extracting entities and relations between these entities, both within and across languages."
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# Summary. An optional shortened abstract.
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summary: ""
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tags: []
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categories: []
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featured: false
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# Custom links (optional).
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# Uncomment and edit lines below to show custom links.
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# links:
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# - name: Follow
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# url: https://twitter.com
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# icon_pack: fab
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# icon: twitter
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url_pdf: "https://aclanthology.org/2024.lrec-main.36.pdf"
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url_code:
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url_dataset:
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url_poster:
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url_project:
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url_slides:
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url_source:
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url_video:
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# Featured image
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# To use, add an image named `featured.jpg/png` to your page's folder.
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# Focal points: Smart, Center, TopLeft, Top, TopRight, Left, Right, BottomLeft, Bottom, BottomRight.
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image:
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caption: ""
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focal_point: ""
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preview_only: false
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# Associated Projects (optional).
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# Associate this publication with one or more of your projects.
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# Simply enter your project's folder or file name without extension.
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# E.g. `internal-project` references `content/project/internal-project/index.md`.
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# Otherwise, set `projects: []`.
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projects: [KEEPHA]
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# Slides (optional).
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# Associate this publication with Markdown slides.
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# Simply enter your slide deck's filename without extension.
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# E.g. `slides: "example"` references `content/slides/example/index.md`.
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# Otherwise, set `slides: ""`.
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slides: ""
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---

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