About the Bibliome Challenges
The Bibliome team at INRAE designs and coordinates evaluation challenges in Natural Language Processing (NLP), focusing on the life sciences, agriculture, and environmental research domains. These initiatives bring together researchers and practitioners from around the world to advance information extraction, text mining, and knowledge discovery from scientific and technical documents.
What is a challenge?
A challenge is an open scientific evaluation where the organizers define one or more tasks and provide reference datasets and clear evaluation metrics.
Participants develop and test their methods on these datasets and submit their predictions for comparison.
All submissions are evaluated with standardized metrics, ensuring a fair and transparent benchmarking process.
Each challenge concludes with a workshop, where teams present their systems and discuss results, encouraging community exchange and collaboration.
Why participate or explore past challenges?
The Bibliome challenges offer a trusted framework for experimentation and reproducible research.
The resulting datasets, reference annotations, and evaluation scripts remain publicly available to encourage training, benchmarking, and methodological comparison.
You can:
Access the datasets and task descriptions used in previous editions;
Explore evaluation results and system performances;
Freely reuse these resources to train or evaluate your own NLP models;
Cite and build upon the challenges for future research.
A reliable organizing team
Hosted at INRAE, France’s national institute for research in agriculture, food, and environment, the Bibliome team has long-standing expertise in corpus creation, information extraction, and evaluation methodology.
Through its coordination of international challenges such as those within the CLEF and BioNLP series, Bibliome contributes to open, data-driven science and to the advancement of language technologies to enhance knowledge acquisition and data-driven research in the life sciences.