Kolmogorov-Arnold Transformer
Xingyi Yang, Xinchao Wang
2025年份
14顶会引用
摘要
Figure 1: (Left) Architecture of standard transformer (e.g. ViT), ViT+KAN which substitutes the MLP with a KAN, and our KAT model. In KAT, the MLP layers in transformers are replaced with GR-KAN layers. (Right) Performance on the ImageNet dataset. KAT * indicates that the model was initialized using a pre-trained ViT. Generally, KAT outperforms both the ViT and DeiT models. ViT+KAN performs poorly on ImageNet-level training.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper14
- Generalization Bounds for Kolmogorov-Arnold Networks (KANs) and Enhanced KANs with Lower Lipschitz ComplexityPengqi Li, Lizhong Ding, Jiarun Fu, Chunhui Zhang 等NeurIPS 2025 · 被引用 8 次
- Efficiency Follows Global-Local DecouplingZhenyu Yang, Gensheng Pei, Tao Chen, Yichao Zhou 等CVPR 2026 · 被引用 3 次
- Unifying Locality of KANs and Feature Drift Compensation Projection for Data-Free Replay Based Continual Face Forgery DetectionTianshuo Zhang, Siran Peng, Li Gao, Haoyuan Zhang 等AAAI 2026 · 被引用 1 次
- Catastrophic Forgetting in Kolmogorov-Arnold NetworksMohammad Marufur Rahman, Guanchu Wang, Kaixiong Zhou, Minghan Chen 等AAAI 2026 · 被引用 1 次
- Polynomial, trigonometric, and tropical activationsIsmail Khalfaoui Hassani, Stefan KesselheimICLR 2026 · 被引用 1 次
它引用的顶会 Paper12
- Swin Transformer: Hierarchical Vision Transformer using Shifted WindowsZe Liu, Yutong Lin, Yue Cao, Han Hu 等ICCV 2021 · 被引用 31,683 次
- An Image is Worth 16x16 Words: Transformers for Image Recognition at ScaleAlexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn 等ICLR 2021 · 被引用 21,477 次
- Training data-efficient image transformers & distillation through attentionHugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa 等ICML 2021 · 被引用 8,974 次
- A ConvNet for the 2020sZhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer 等CVPR 2022 · 被引用 6,782 次
- CutMix: Regularization Strategy to Train Strong Classifiers With Localizable FeaturesSangdoo Yun, Dongyoon Han, Sanghyuk Chun, Seong Joon Oh 等ICCV 2019 · 被引用 5,843 次
相关 Paper
- ViTGAN: Training GANs with Vision TransformersKwonjoon Lee, Huiwen Chang, Lu Jiang, Han Zhang 等ICLR 2022 · 被引用 225 次
- Do Vision Transformers See Like Convolutional Neural Networks?Maithra Raghu, Thomas Unterthiner, Simon Kornblith, Chiyuan Zhang 等NeurIPS 2021 · 被引用 1,553 次
- CvT: Introducing Convolutions to Vision TransformersHaiping Wu, Bin Xiao, Noel Codella, Mengchen Liu 等ICCV 2021 · 被引用 2,397 次
- Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNetLi Yuan, Yunpeng Chen, Tao Wang, Weihao Yu 等ICCV 2021 · 被引用 2,462 次
- Incorporating Convolution Designs into Visual TransformersKun Yuan, Shaopeng Guo, Ziwei Liu, Aojun Zhou 等ICCV 2021 · 被引用 581 次
