A Smaller Transformer in Your Transformer

The paper introduces Transformer-Within-Transformer (TWT), a post‑hoc technique that merges contiguous redundant layers in Vision Transformers into a single surrogate layer. By doing so, TWT cuts both parameter count and inference compute while maintaining competitive performance on natural image tasks with only half the depth. In histopathology applications, TWT not only matches but sometimes surpasses the baseline model’s performance.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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