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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| 2020 |
| arxiv 2006.14536 |
| FREE: Feature Refinement for Generalized Zero-Shot Learning | Shiming Chen, Wenjie Wang, Beihao Xia | 2021 | arxiv 2107.13807 |
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| SIAM: Chiplet-based Scalable In-Memory Acceleration with Mesh for Deep Neural Networks | Gokul Krishnan, Sumit K. Mandal, Manvitha Pannala | 2021 | arxiv 2108.08903 |
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| Damage detection using in-domain and cross-domain transfer learning | Zaharah A. Bukhsh, Nils Jansen, Aaqib Saeed | 2021 | arxiv 2102.03858 |
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| A Closer Look at Few-Shot Video Classification: A New Baseline and Benchmark | Zhenxi Zhu, Limin Wang, Sheng Guo | 2021 | arxiv 2110.12358 |
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| Why Do Better Loss Functions Lead to Less Transferable Features? | Simon Kornblith, Ting Chen, Honglak Lee | 2020 | arxiv 2010.16402 |
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| A Framework for Learning Ante-hoc Explainable Models via Concepts | Anirban Sarkar, Deepak Vijaykeerthy, Anindya Sarkar | 2021 | arxiv 2108.11761 |
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| Input-Specific Robustness Certification for Randomized Smoothing | Ruoxin Chen, Jie Li, Junchi Yan | 2021 | arxiv 2112.12084 |
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| BMPQ: Bit-Gradient Sensitivity Driven Mixed-Precision Quantization of DNNs from Scratch | Souvik Kundu, Shikai Wang, Qirui Sun | 2021 | arxiv 2112.13843 |
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| Robust Contrastive Learning Using Negative Samples with Diminished Semantics | Songwei Ge, Shlok Mishra, Haohan Wang | 2021 | arxiv 2110.14189 |
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| Fixing the train-test resolution discrepancy | Hugo Touvron, Andrea Vedaldi, Matthijs Douze | 2019 | arxiv 1906.06423 |
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