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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| MaxViT: Multi-Axis Vision Transformer |
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| Zhengzhong Tu, Hossein Talebi, Han Zhang |
| 2022 |
| arxiv 2204.01697 |
| Terrain-Informed Self-Supervised Learning: Enhancing Building Footprint Extraction from LiDAR Data with Limited Annotations | Anuja Vats, David Völgyes, Martijn Vermeer | 2023 | arxiv 2311.01188 |
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| A Study on Self-Supervised Pretraining for Vision Problems in Gastrointestinal Endoscopy | Edward Sanderson, Bogdan J. Matuszewski | 2024 | arxiv 2401.06278 |
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| CMT: Mid-Training for Efficient Learning of Consistency, Mean Flow, and Flow Map Models | Zheyuan Hu, Chieh-Hsin Lai, Yuki Mitsufuji | 2025 | arxiv 2509.24526 |
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| Selfie: Self-supervised Pretraining for Image Embedding | Trieu H. Trinh, Minh-Thang Luong, Quoc V. Le | 2019 | arxiv 1906.02940 |
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| Learning Representations with Contrastive Self-Supervised Learning for Histopathology Applications | Karin Stacke, Jonas Unger, Claes Lundström | 2021 | arxiv 2112.05760 |
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| Generating Images with 3D Annotations Using Diffusion Models | Wufei Ma, Qihao Liu, Jiahao Wang | 2023 | arxiv 2306.08103 |
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| Matryoshka Representation Learning | Aditya Kusupati, Gantavya Bhatt, Aniket Rege | 2022 | arxiv 2205.13147 |
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| Beyond neural scaling laws: beating power law scaling via data pruning | Ben Sorscher, Robert Geirhos, Shashank Shekhar | 2022 | arxiv 2206.14486 |
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| Uncovering the effects of model initialization on deep model generalization: A study with adult and pediatric Chest X-ray images | Sivaramakrishnan Rajaraman, Ghada Zamzmi, Feng Yang | 2023 | arxiv 2309.11318 |
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