RAM-APL combines distance rankings and pseudo-class label accuracy from two foundation models to select training subsets, outperforming twelve baselines on fine-grained image datasets.
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Foundation Model Insights and a Multi-Model Approach for Superior Fine-Grained One-shot Subset Selection
RAM-APL combines distance rankings and pseudo-class label accuracy from two foundation models to select training subsets, outperforming twelve baselines on fine-grained image datasets.