datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Latent-Resonance-AI-Image-Forensics-Benchmark-N100
Latent Resonance: SOTA Empirical AI Image Forensics Benchmark (N=100 & N=1,000 Scale)
Author: Debdip Bandyopadhyay (Independent AI Researcher, Kolkata, India; M.Tech, IIT Jodhpur, AI & Data Science)Preprint & Paper: Latent Resonance: Zero-Shot Autoencoder Inversion and Azimuthal Spectral Forensics for Diffusion Image Attribution (IEEE Flagship / CERN Zenodo 2026)
Benchmark Overview
This repository provides:
The official verified $N=100$ ground-truth image… See the full description on the dataset page: https://huggingface.co/datasets/DebdipCS/Latent-Resonance-AI-Image-Forensics-Benchmark-N100.solar-flare-hmi-datasplitsThis dataset is intended to be used for training/testing solar flare forecasting models. It contains various data splits (in json format) of SDO/HMI magnetogram images compiled by
Boucheron, L.E., et al., 2023, Sci Data 10, 825, https://doi.org/10.1038/s41597-023-02628-8.
Splits "train", "val", "test" corresponds to the original data splits provided by Boucheron et al., while the other splits are created by downsampling the No-Flare and C flare class to obtain
more balanced splits and… See the full description on the dataset page: https://huggingface.co/datasets/inaf-oact-ai/solar-flare-hmi-datasplits.aiconf-butterfly-learn-for-model-to-markupMaster dataset for the next markup stage of butterfly detection.
Sampling rules:
500 butterfly images
500 negative images
negative classes are distributed uniformly across: bee, beetle, flower, shrub
Files:
master_dataset.json
master_dataset.tsv
Columns:
photo_id
image
entity
selection_group
target_label
needs_bbox_markup
source_split
hard (if present in source)
photo_url (if present in source)
taxon (if present in source)
Source dataset: vsevolod-nv/aiconf-butterfly-detection-all… See the full description on the dataset page: https://huggingface.co/datasets/vsevolod-nv/aiconf-butterfly-learn-for-model-to-markup.aidm-dogs-vs-cats-results
aidm-dogs-vs-cats-results
The experiment record of a dogs-vs-cats image-classification study, with CIFAR-10 and CIFAR-10-LT transfer and class-imbalance ablations. This repo holds the run registry, the splits, the report tables and figures, and the per-run predicted probabilities. It holds no images and no model weights; the checkpoints are in the companion model repo.
Generated by scripts/90_publish_hf.py on 2026-09-22 19:17 UTC. Every count, fingerprint and metric below was… See the full description on the dataset page: https://huggingface.co/datasets/ngqtrung/aidm-dogs-vs-cats-results.visual_ai_at_neurips2025_jina
Dataset Card for Voxel51/visual_ai_at_neurips2025
This is a FiftyOne dataset with 1134 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("harpreetsahota/visual_ai_at_neurips2025_jina")
# Launch the App
session =… See the full description on the dataset page: https://huggingface.co/datasets/harpreetsahota/visual_ai_at_neurips2025_jina.aiconf-butterfly-detection-goldenset-extendedExtended goldenset for butterfly detection built from the original goldenset and a validated expansion pass.
Files:
larger_goldenset.json
larger_goldenset.tsv
Columns:
photo_id
image
entity
bbox
Generated at: 2026-04-19 23:31:19 UTC
Rows: 356
visual_ai_at_neurips2025_nomic
Dataset Card for Voxel51/visual_ai_at_neurips2025
This is a FiftyOne dataset with 1134 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("harpreetsahota/visual_ai_at_neurips2025_nomic")
# Launch the App
session =… See the full description on the dataset page: https://huggingface.co/datasets/harpreetsahota/visual_ai_at_neurips2025_nomic.aiconf-butterfly-detection-allColumns:
taxon
photo_id
photo_url
hard
Dataset dedicated to further butterfly segmentation in the wild. The dataset contains photos of butterflies, bees, beetles, flowers, and shrubs, collected from iNaturalist.
The hard column indicates whether the photo is considered a hard example for butterfly detection according to a few CV techniques.
Generated at: 2026-03-15 16:40:21 UTC
Rows: 1800
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