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Invertible zero-shot recognition flows. In Computer Vision--ECCV 2020: 16th European Conference, Glasgow, UK, August 23--28, 2020, Proceedings, Part XVI 16. Springer, 614--631."},{"key":"e_1_3_2_1_58_1","volume-title":"Proceedings of the International Conference on Machine Learning (ICML).","author":"Smith John","year":"2023","unstructured":"John Smith and Alice Doe. 2023. Advances in Regularization Techniques for Embedding-Based Zero-Shot Learning. In Proceedings of the International Conference on Machine Learning (ICML)."},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00113"},{"key":"e_1_3_2_1_60_1","volume-title":"Avinava Dubey, and Vikas Sindhwani.","author":"Varley Jake","year":"2024","unstructured":"Jake Varley, Sumeet Singh, Deepali Jain, Krzysztof Choromanski, Andy Zeng, Somnath Basu Roy Chowdhury, Avinava Dubey, and Vikas Sindhwani. 2024. 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