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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| Deeply Coupled Cross-Modal Prompt Learning |
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| Xuejing Liu, Wei Tang, Jinghui Lu |
| 2023 |
| arxiv 2305.17903 |
| R-FCN: Object Detection via Region-based Fully Convolutional Networks | Jifeng Dai, Yi Li, Kaiming He | 2016 | arxiv 1605.06409 |
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| Improving Cross-domain Few-shot Classification with Multilayer Perceptron | Shuanghao Bai, Wanqi Zhou, Zhirong Luan | 2023 | arxiv 2312.09589 |
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| Operator-learning-inspired Modeling of Neural Ordinary Differential Equations | Woojin Cho, Seunghyeon Cho, Hyundong Jin | 2023 | arxiv 2312.10274 |
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| Supervision Interpolation via LossMix: Generalizing Mixup for Object Detection and Beyond | Thanh Vu, Baochen Sun, Bodi Yuan | 2023 | arxiv 2303.10343 |
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| Let's Agree to Agree: Neural Networks Share Classification Order on Real Datasets | Guy Hacohen, Leshem Choshen, Daphna Weinshall | 2019 | arxiv 1905.10854 |
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| RL-LOGO: Deep Reinforcement Learning Localization for Logo Recognition | Masato Fujitake | 2023 | arxiv 2312.16792 |
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| CLAF: Contrastive Learning with Augmented Features for Imbalanced Semi-Supervised Learning | Bowen Tao, Lan Li, Xin-Chun Li | 2023 | arxiv 2312.09598 |
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| Chordal Sparsity for Lipschitz Constant Estimation of Deep Neural Networks | Anton Xue, Lars Lindemann, Alexander Robey | 2022 | arxiv 2204.00846 |
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| Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design | Ibrahim Alabdulmohsin, Xiaohua Zhai, Alexander Kolesnikov | 2023 | arxiv 2305.13035 |
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