datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
SDS-KoPub-VDR-Benchmark
📘 Dataset Summary
SDS KoPub-VDR is a benchmark dataset for Visual Document Retrieval (VDR) in the context of
Korean public documents. It contains real-world government document images paired with natural-language
queries, corresponding answer pages, and ground-truth answers. The dataset is designed to evaluate AI models that
go beyond simple text matching, requiring comprehensive understanding of visual layouts, tables, graphs, and images
to accurately locate relevant… See the full description on the dataset page: https://huggingface.co/datasets/SamsungSDS-Research/SDS-KoPub-VDR-Benchmark.samson
Description
Samson is a simple dataset that is available from the website. In this image, there are 952x952 pixels. Each pixel is recorded at 156 channels covering the wavelengths from 401 nm to 889 nm. The spectral resolution is highly up to 3.13 nm. As the original image is too large, which is very expensive in terms of computational cost, a region of 95x95 pixels is used. It starts from the (252,332)-th pixel in the original image. This data is not degraded by the blank channel… See the full description on the dataset page: https://huggingface.co/datasets/danaroth/samson.SAM-SGT
SGT: Semantic Generative Tuning for Unified Multimodal Models
This repository hosts checkpoints fine-tuned with Semantic Generative Tuning (SGT) — a training
paradigm that couples visual understanding and generation in Unified Multimodal Models (UMMs)
by using image segmentation as a generative proxy.
Unified multimodal models typically optimize understanding and generation with misaligned
objectives (sparse text tokens vs. dense pixel targets), which isolates the two capabilities.… See the full description on the dataset page: https://huggingface.co/datasets/Two-hot/SAM-SGT.SkifiSAMSEMO-ENUNOFFICIAL MIRROR OF THE SAMSEMO DATASET
[https://github.com/pawel-bujnowski/samsemo]
[https://www.isca-archive.org/interspeech_2024/bujnowski24_interspeech.pdf]
All copyright belongs to the original authors
samsung-phones-datasettwitter-SamsulSaputraa-2025.09.22-1970145075847135278-u1iNIH9PJJnxPKFH-part1samsung-vlm-datasetsamson
Description
Samson is a simple dataset that is available from the website. In this image, there are 952x952 pixels. Each pixel is recorded at 156 channels covering the wavelengths from 401 nm to 889 nm. The spectral resolution is highly up to 3.13 nm. As the original image is too large, which is very expensive in terms of computational cost, a region of 95x95 pixels is used. It starts from the (252,332)-th pixel in the original image. This data is not degraded by the blank channel… See the full description on the dataset page: https://huggingface.co/datasets/taowang1122333/samson.image_samsungMafasamson
Description
Samson is a simple dataset that is available from the website. In this image, there are 952x952 pixels. Each pixel is recorded at 156 channels covering the wavelengths from 401 nm to 889 nm. The spectral resolution is highly up to 3.13 nm. As the original image is too large, which is very expensive in terms of computational cost, a region of 95x95 pixels is used. It starts from the (252,332)-th pixel in the original image. This data is not degraded by the blank channel… See the full description on the dataset page: https://huggingface.co/datasets/jettedjj/samson.fennec