ITNet collapses CNNs, Transformers and RNNs into one learnable integral transform
ITNet introduces a learnable integral transform that subsumes convolution, self‑attention, and recurrence. By using a small MLP‑based kernel, a single model matches or beats specialized CNN, Transformer, and RNN baselines on ImageNet, GLUE, ModelNet40, VQA v2 and NLVR2, proving a unified operator can replace three architectural families.