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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| Wilkie Olin-Ammentorp Maxim Bazhenov |
| 2022 |
| arxiv 2207.08953 |
| The Randomness of Input Data Spaces is an A Priori Predictor for Generalization | Martin Briesch, Dominik Sobania, Franz Rothlauf | 2021 | arxiv 2106.04181 |
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| Contrastive Learning for OOD in Object detection | Rishab Balasubramanian, Rupashree Dey, Kunal Rathore | 2022 | arxiv 2208.06083 |
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| Probing Contextual Diversity for Dense Out-of-Distribution Detection | Silvio Galesso, Maria Alejandra Bravo, Mehdi Naouar | 2022 | arxiv 2208.14195 |
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| Privacy Enhancement for Cloud-Based Few-Shot Learning | Archit Parnami, Muhammad Usama, Liyue Fan | 2022 | arxiv 2205.07864 |
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| Feature-level augmentation to improve robustness of deep neural networks to affine transformations | Adrian Sandru, Mariana-Iuliana Georgescu, Radu Tudor Ionescu | 2022 | arxiv 2202.05152 |
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| Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks | Wenhui Wang, Hangbo Bao, Li Dong | 2022 | arxiv 2208.10442 |
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| A Unified Framework with Meta-dropout for Few-shot Learning | Shaobo Lin, Xingyu Zeng, Rui Zhao | 2022 | arxiv 2210.06409 |
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| XNAS: Neural Architecture Search with Expert Advice | Niv Nayman, Asaf Noy, Tal Ridnik | 2019 | arxiv 1906.08031 |
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| Tight Certified Robustness via Min-Max Representations of ReLU Neural Networks | Brendon G. Anderson, Samuel Pfrommer, Somayeh Sojoudi | 2023 | arxiv 2310.04916 |
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