BioNLP Workshop

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SIGBIOMED | BioNLP 2023


BIONLP 2024 and Shared Tasks @ ACL 2024

The 23rd BioNLP workshop associated with the ACL SIGBIOMED special interest group is co-located with ACL 2024


IMPORTANT DATES

Coming soon


SUBMISSION INSTRUCTIONS

Two types of submissions are invited: full (long) papers and short papers.

Submission site for the workshop COMING SOON

WORKSHOP OVERVIEW AND SCOPE

The BioNLP workshop, associated with the ACL SIGBIOMED special interest group, is an established primary venue for presenting research in language processing and language understanding for the biological and medical domains. The workshop has been running every year since 2002 and continues getting stronger. Many other emerging biomedical and clinical language processing workshops can afford to be more specialized because BioNLP truly encompasses the breadth of the domain and brings together researchers in bio- and clinical NLP from all over the world.

BioNLP 2024 will be particularly interested in transparency of the generative approaches and factuality of the generated text. Language processing that supports DEIA (Diversity, Equity, Inclusion and Accessibility) is still of utmost importance. The work on detection and mitigation of bias and misinformation continues to be of interest. Research in languages other than English, particularly, under-represented languages, and health disparities are always of interest to BioNLP. Other active areas of research include, but are not limited to:

  • Tangible results of biomedical language processing applications;
  • Entity identification and normalization (linking) for a broad range of semantic categories;
  • Extraction of complex relations and events;
  • Discourse analysis; Anaphora \& coreference resolution;
  • Text mining \& Literature based discovery;
  • Summarization;
  • Text simplification;
  • Question Answering;
  • Resources and strategies for system testing and evaluation;
  • Infrastructures and pre-trained language models for biomedical NLP;
  • Processing and annotation platforms;
  • Synthetic data generation \& data augmentation;
  • Translating NLP research into practice;
  • Getting reproducible results.

Organizers

 * Dina Demner-Fushman, US National Library of Medicine
 * Sophia Ananiadou, National Centre for Text Mining and University of Manchester, UK
 * Makoto Miwa, Toyota Technological Institute, Japan
 * Kirk Roberts, UTHealth, Houston, Texas
 * Jun-ichi Tsujii, National Institute of Advanced Industrial Science and Technology, Japan