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Transductive Learning for Textual Few-Shot Classification in API-based Embedding Models.

, , , , , , and . EMNLP, page 4214-4231. Association for Computational Linguistics, (2023)

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FHIST: A Benchmark for Few-shot Classification of Histological Images., , , , , , and . CoRR, (2022)Realistic evaluation of transductive few-shot learning., , , and . NeurIPS, page 9290-9302. (2021)Open-Set Likelihood Maximization for Few-Shot Learning., , , , , , and . CVPR, page 24007-24016. IEEE, (2023)A Unifying Mutual Information View of Metric Learning: Cross-Entropy vs. Pairwise Losses., , , , , , and . ECCV (6), volume 12351 of Lecture Notes in Computer Science, page 548-564. Springer, (2020)Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?, , , , , and . CoRR, (2020)Simplex Clustering via sBeta with Applications to Online Adjustment of Black-Box Predictions., , , and . CoRR, (2022)Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?, , , , , and . CVPR, page 13979-13988. Computer Vision Foundation / IEEE, (2021)Parameter-free Online Test-time Adaptation., , , and . CVPR, page 8334-8343. IEEE, (2022)Transductive Learning for Textual Few-Shot Classification in API-based Embedding Models., , , , , , and . EMNLP, page 4214-4231. Association for Computational Linguistics, (2023)Transductive Information Maximization For Few-Shot Learning., , , , , and . CoRR, (2020)