Agglomerative Token Clustering

• URL: http://arxiv.org/abs/2409.11923v1
• Date: Wed, 18 Sep 2024 12:37:58 GMT
• Title: Agglomerative Token Clustering
• Authors: Joakim Bruslund Haurum, Sergio Escalera, Graham W. Taylor, Thomas B. Moeslund,
• Abstract summary: Agglomerative Token Clustering (ATC) is a novel token merging method that consistently outperforms previous methods. We find that ATC achieves state-of-the-art performance across all tasks, and can even perform on par with prior state-of-the-art when applied off-the-shelf.
• Score: 61.0477253613511
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present Agglomerative Token Clustering (ATC), a novel token merging method that consistently outperforms previous token merging and pruning methods across image classification, image synthesis, and object detection & segmentation tasks. ATC merges clusters through bottom-up hierarchical clustering, without the introduction of extra learnable parameters. We find that ATC achieves state-of-the-art performance across all tasks, and can even perform on par with prior state-of-the-art when applied off-the-shelf, i.e. without fine-tuning. ATC is particularly effective when applied with low keep rates, where only a small fraction of tokens are kept and retaining task performance is especially difficult.

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