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Learning to Answer by Learning to Ask: Getting the Best of GPT-2 and BERT Worlds

, and . (2019)cite arxiv:1911.02365.

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Fast but Not Deep: Efficient Crowd Abnormality Detection with Local Binary Tracklets., , , , and . AVSS, page 1-6. IEEE, (2018)Self Paced Adversarial Training for Multimodal Few-shot Learning., , , , and . CoRR, (2018)Training Adversarial Discriminators for Cross-Channel Abnormal Event Detection in Crowds., , , and . WACV, page 1896-1904. IEEE, (2019)Novel dataset for fine-grained abnormal behavior understanding in crowd., , , , , and . AVSS, page 95-101. IEEE Computer Society, (2016)Attention Is (not) All You Need for Commonsense Reasoning., and . ACL (1), page 4831-4836. Association for Computational Linguistics, (2019)Learning with dataset bias in latent subcategory models., , , , , and . CVPR, page 3650-3658. IEEE Computer Society, (2015)Learning to Answer by Learning to Ask: Getting the Best of GPT-2 and BERT Worlds, and . (2019)cite arxiv:1911.02365.A Unified Objective for Novel Class Discovery., , , , , and . ICCV, page 9264-9272. IEEE, (2021)EaSe: A Diagnostic Tool for VQA based on Answer Diversity., , and . NAACL-HLT, page 2407-2414. Association for Computational Linguistics, (2021)Multimodal Prototypical Networks for Few-shot Learning., , , and . WACV, page 2643-2652. IEEE, (2021)