datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
lgg-mri-segmentation-research
LGG Brain MRI Segmentation with Genomic Clusters
This repository provides a Patient-Centric version of the Lower-Grade Glioma (LGG) Segmentation dataset. While other versions of this data exist, they often treat slices as independent images. This version preserves the 3D patient volume and integrates all genomic/clinical labels directly into a multimodal-ready format.
🌟 Why This Version?
Developed for Multimodal AI Research, this dataset addresses several limitations… See the full description on the dataset page: https://huggingface.co/datasets/Ehsan-rmz/lgg-mri-segmentation-research.lgg-mri-segmentation-research
LGG Brain MRI Segmentation with Genomic Clusters
This repository provides a Patient-Centric version of the Lower-Grade Glioma (LGG) Segmentation dataset. While other versions of this data exist, they often treat slices as independent images. This version preserves the 3D patient volume and integrates all genomic/clinical labels directly into a multimodal-ready format.
🌟 Why This Version?
Developed for Multimodal AI Research, this dataset addresses several limitations… See the full description on the dataset page: https://huggingface.co/datasets/vpasx/lgg-mri-segmentation-research.radread-public-results
RadRead — public results
Rollout-level results for RadRead, a benchmark of frontier models reading 150
radiographs. Every row is one graded model read: 5 saved rollouts per study
per model, scored by a deterministic grader (no judge model).
A read passes only when every required checklist finding, lesion box (the grader's
IoU / centre / containment test), lexical diagnosis check and action-set membership
check match the reference rubric. No partial credit inside a study;… See the full description on the dataset page: https://huggingface.co/datasets/tirandazdylan/radread-public-results.Latent-Resonance-AI-Image-Forensics-Benchmark-N1000
Latent Resonance: SOTA Large-Scale AI Image Forensics Benchmark (N=1,000)
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)
1. Executive Summary & Diagnostic Suite
This repository contains the complete empirical evaluation records… See the full description on the dataset page: https://huggingface.co/datasets/DebdipCS/Latent-Resonance-AI-Image-Forensics-Benchmark-N1000.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.