What is VQA? VQA is a new dataset containing open-ended questions about images. These questions require an understanding of vision, language and commonsense knowledge to answer. 265,016 images (COCO and abstract scenes) At least 3 questions (5.4 questions on average) per image 10 ground truth answers per question 3 plausible...
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Sponsors Description ImageCLEF aims to provide an evaluation forum for the cross–language annotation and retrieval of images. Motivated by the need to support multilingual users from a global community accessing the ever growing body of visual information, the main goal of ImageCLEF is to support the advancement of the field...
Question Answering in Context (QuAC) is a dataset for modeling, understanding, and participating in information seeking dialog. Data instances consist of an interactive dialog between two crowd workers: (1) a student who poses a sequence of freeform questions to learn as much as possible about a hidden Wikipedia text, and (2) a teacher who answers the questions by providing short excerpts (spans) from the text. QuAC introduces challenges not found in existing machine comprehension datasets: its questions are often more open-ended, unanswerable, or only meaningful within the dialog context.
The Office of HIV/AIDS Network Coordination (HANC) works with the HIV/AIDS Clinical Trials Networks of the U.S. National Institutes of Health (NIH) with the intent of creating a more integrated, collaborative and flexible research structure.