Rethinking-Large-scale-Dataset-Compression
Collection
Distilled and pruning datasets used in the paper "Rethinking Large-scale Dataset Compression: Shifting Focus From Labels to Images"
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Dataset used for paper -> "Rethinking Dataset Compression: Shifting Focus From Labels to Images"
Dataset created according to the paper Identifying Mislabeled Data using the Area Under the Margin Ranking.
Basic Usage
from datasets import load_dataset
dataset = load_dataset("he-yang/2025-rethinkdc-imagenet-aum-ipc-50")
For more information, please refer to the Rethinking-Dataset-Compression
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Size of downloaded dataset files:
3.71 GB
Size of the auto-converted Parquet files:
3.71 GB
Number of rows:
50,000