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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| Ninnart Fuengfusin, Hakaru Tamukoh |
| 2024 |
| arxiv 2411.19027 |
| Contemplating real-world object classification | Ali Borji | 2021 | arxiv 2103.05137 |
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| Learning Self-Regularized Adversarial Views for Self-Supervised Vision Transformers | Tao Tang, Changlin Li, Guangrun Wang | 2022 | arxiv 2210.08458 |
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| Data Filtering Networks | Alex Fang, Albin Madappally Jose, Amit Jain | 2023 | arxiv 2309.17425 |
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| Transitive Invariance for Self-supervised Visual Representation Learning | Xiaolong Wang, Kaiming He, Abhinav Gupta | 2017 | arxiv 1708.02901 |
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| ADPretrain: Advancing Industrial Anomaly Detection via Anomaly Representation Pretraining | Xincheng Yao, Yan Luo, Zefeng Qian | 2025 | arxiv 2511.05245 |
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| MOAT: Alternating Mobile Convolution and Attention Brings Strong Vision Models | Chenglin Yang, Siyuan Qiao, Qihang Yu | 2022 | arxiv 2210.01820 |
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| Scaling Text-to-Image Diffusion Transformers with Representation Autoencoders | Shengbang Tong, Boyang Zheng, Ziteng Wang | 2026 | arxiv 2601.16208 |
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| BiGain: Unified Token Compression for Joint Generation and Classification | Jiacheng Liu, Shengkun Tang, Jiacheng Cui | 2026 | arxiv 2603.12240 |
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| Task Relevance Is Not Local Replaceability: A Two-Axis View of Channel Information | Houman Safaai, Andrew T. Landau, Celia C. Beron | 2026 | arxiv 2605.07086 |
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