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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| arxiv 2303.12001 |
| Only My Model On My Data: A Privacy Preserving Approach Protecting one Model and Deceiving Unauthorized Black-Box Models | Weiheng Chai, Brian Testa, Huantao Ren | 2024 | arxiv 2402.09316 |
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| CLAMP: Contrastive LAnguage Model Prompt-tuning | Piotr Teterwak, Ximeng Sun, Bryan A. Plummer | 2023 | arxiv 2312.01629 |
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| Neural Optimizer Equation, Decay Function, and Learning Rate Schedule Joint Evolution | Brandon Morgan, Dean Hougen | 2024 | arxiv 2404.06679 |
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| ContraCluster: Learning to Classify without Labels by Contrastive Self-Supervision and Prototype-Based Semi-Supervision | Seongho Joe, Byoungjip Kim, Hoyoung Kang | 2023 | arxiv 2304.09369 |
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| DeBiFormer: Vision Transformer with Deformable Agent Bi-level Routing Attention | Nguyen Huu Bao Long, Chenyu Zhang, Yuzhi Shi | 2024 | arxiv 2410.08582 |
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| On the Cost of Model-Serving Frameworks: An Experimental Evaluation | Pasquale De Rosa, Yérom-David Bromberg, Pascal Felber | 2024 | arxiv 2411.10337 |
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| Grouped Sequential Optimization Strategy -- the Application of Hyperparameter Importance Assessment in Deep Learning | Ruinan Wang, Ian Nabney, Mohammad Golbabaee | 2025 | arxiv 2503.05106 |
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| On the Robustness of Kolmogorov-Arnold Networks: An Adversarial Perspective | Tal Alter, Raz Lapid, Moshe Sipper | 2024 | arxiv 2408.13809 |
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| HS-ResNet: Hierarchical-Split Block on Convolutional Neural Network | Pengcheng Yuan, Shufei Lin, Cheng Cui | 2020 | arxiv 2010.07621 |
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| Synergic Adversarial Label Learning for Grading Retinal Diseases via Knowledge Distillation and Multi-task Learning | Lie Ju, Xin Wang, Xin Zhao | 2020 | arxiv 2003.10607 |
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