Welcome to the RAIVN Lab
The Reasoning, AI and VisioN (RAIVN) Lab at Paul G. Allen School of Computer Science and Engineering, University of Washington is directed by Prof. Ali Farhadi. Our research is at the intersection of Computer Vision, Machine Learning, Natural Language Processing and Robotics and is targetted towards helping computers improve their perception and reasoning. RAIVN Lab's famous research break-throughs include YOLO, XNor-Net, VCR, BiDAF among many other amazing projects.
Recent News
- September 2022: 3 papers accepted to NeurIPS 2022.
- July 2022: 2 papers accepted to ECCV 2022 and 1 paper at NAACL 2022.
- June 2022: Robust fine-tuning of zero-shot models wins Best Paper Honorable Mention at CVPR 2022.
- May 2022: 3 papers accepted to CVPR 2022 and 1 paper at ICML 2022.
- March 2022: Model soups achieve the new current best accuracy on ImageNet. Older News
Sponsors
@RAIVNLab
@RAIVNLabVisit Us
CSE2 230,
Bill & Melinda Gates Center For Computer Science & Engineering,
Paul G. Allen School of Computer Science & Engineering,
University of Washington, Seattle, WA 98195.
Bill & Melinda Gates Center For Computer Science & Engineering,
Paul G. Allen School of Computer Science & Engineering,
University of Washington, Seattle, WA 98195.
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