--- viewer: false tags: - adversarial-robustness - image-classification - robustness-benchmark --- # RobustGenBench-sample This is a **stratified sample** of the full [RobustGenBench](https://huggingface.co/datasets/legolasflagstaff/RobustGenBench) dataset (22 GB), created for NeurIPS dataset submission review. ## Structure Each subfolder contains **2 images per class** extracted from the corresponding archive in the full dataset, plus `test/labels.csv` and `metadata.json`. ``` clean/ caltech101/ ← 2 imgs/class × 101 classes = 202 images fgvc-aircraft-2013b/ flowers-102/ oxford-iiit-pet/ stanford_cars/ uc-merced-land-use-dataset/ adversarial/ common/common_severity3// random/linf_eps30_random_uniform// zeroshot_clip_vitb16_laion2b/// zeroshot_clip_vith14_laion2b/// zeroshot_metaclip_vith14_fullcc2_5b/// zeroshot_siglip2_base_patch16_224/// zeroshot_siglip2_so400m_patch14_384/// zeroshot_siglip2_so400m_patch16_naflex/// zeroshot_siglip2_so400m_patch16_naflex_patchify/// ``` Each leaf folder has the same internal layout: - `test/labels.csv` — `filename,label` mapping (integer class indices) - `test/NNNNN.png` — flat-numbered PNG images (same filenames across clean & adversarial) - `metadata.json` — split counts (clean archives only) Class name mappings are in `class_names/.json`. See **[SAMPLE.md](SAMPLE.md)** for full details on sampling methodology. ## Full dataset 👉 https://huggingface.co/datasets/legolasflagstaff/RobustGenBench