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Efficient Contextual Representation Learning With Continuous Outputs.

, , , and . Trans. Assoc. Comput. Linguistics, (2019)

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SGEITL: Scene Graph Enhanced Image-Text Learning for Visual Commonsense Reasoning., , , , , , , and . AAAI, page 5914-5922. AAAI Press, (2022)Efficient Contextual Representation Learning With Continuous Outputs., , , and . Trans. Assoc. Comput. Linguistics, (2019)How Much Can CLIP Benefit Vision-and-Language Tasks?, , , , , , , and . ICLR, OpenReview.net, (2022)Grounded Language-Image Pre-training., , , , , , , , , and 2 other author(s). CVPR, page 10955-10965. IEEE, (2022)RegionCLIP: Region-based Language-Image Pretraining., , , , , , , , , and 1 other author(s). CVPR, page 16772-16782. IEEE, (2022)MetaVL: Transferring In-Context Learning Ability From Language Models to Vision-Language Models., , , , and . ACL (2), page 495-508. Association for Computational Linguistics, (2023)What Does BERT with Vision Look At?, , , , and . ACL, page 5265-5275. Association for Computational Linguistics, (2020)Broaden the Vision: Geo-Diverse Visual Commonsense Reasoning., , , , and . EMNLP (1), page 2115-2129. Association for Computational Linguistics, (2021)BERTHop: An Effective Vision-and-Language Model for Chest X-ray Disease Diagnosis., , , , , and . MICCAI (5), volume 13435 of Lecture Notes in Computer Science, page 725-734. Springer, (2022)GeoMLAMA: Geo-Diverse Commonsense Probing on Multilingual Pre-Trained Language Models., , , , and . EMNLP, page 2039-2055. Association for Computational Linguistics, (2022)