Open Source
Open-source initiatives are democratizing access to and accelerating advancements in various scientific and technological fields by fostering collaboration and reproducibility. Current research focuses on developing open-source tools and datasets across diverse domains, including AI models (like LLMs and specialized models for tasks such as medical diagnosis or autonomous driving), simulation environments for robotics and network analysis, and benchmarks for evaluating model performance. This open approach significantly benefits the scientific community by enabling wider participation, facilitating rigorous validation, and accelerating the translation of research into practical applications across numerous sectors.
Papers
Releasing the CRaQAn (Coreference Resolution in Question-Answering): An open-source dataset and dataset creation methodology using instruction-following models
Rob Grzywinski, Joshua D'Arcy, Rob Naidoff, Ashish Shukla, Alex Browne, Ren Gibbons, Brinnae Bent
Syn3DWound: A Synthetic Dataset for 3D Wound Bed Analysis
Léo Lebrat, Rodrigo Santa Cruz, Remi Chierchia, Yulia Arzhaeva, Mohammad Ali Armin, Joshua Goldsmith, Jeremy Oorloff, Prithvi Reddy, Chuong Nguyen, Lars Petersson, Michelle Barakat-Johnson, Georgina Luscombe, Clinton Fookes, Olivier Salvado, David Ahmedt-Aristizabal