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Image-text pairs, instruction tuning, visual QA, cross-modal data, foundation model training data
1,534 datasets
Over 15 million data points covering math, code, knowledge, and instruction following form the full set of core-domain SFT data used for post-training the MiniCPM5-1B-SFT model. This dataset is a key representative of L3 refined data within the UltraData L0-L4 tiered data management framework. It was authored by openbmb and last updated on Hugging Face in May 2026.
A research protocol for a cross-sectional study comparing 30 individuals with schizophrenia and 30 healthy controls. The study, authored by Peipei Luan, involves behavioral interoceptive tasks, clinical symptom ratings, cognitive testing, and multimodal MRI scanning. The protocol was last updated on 2026-04-17.
A multimodal dataset combines sequential CTA slices and six clinical biomarkers from 263 symptomatic abdominal aortic aneurysm patients. It was created by Jiaxin Cheng for developing and validating a deep learning model for rupture risk assessment. The dataset was last updated in April 2026.
A retrospective cohort of 263 symptomatic abdominal aortic aneurysm (AAA) patients, with data split into a 230-patient development cohort and a 33-patient independent temporal test set. This multimodal dataset combines sequential computed tomography angiography (CTA) slices with six key clinical biomarkers, created by Jiaxin Cheng and published in April 2026 to develop a deep learning model for predicting impending rupture.
A set of benchmark functions used to evaluate the Felis Catus Optimization (FCO) metaheuristic algorithm. The dataset includes functions from the CEC 2005 and CEC 2017 benchmark suites. It was created by Mohammad Salehi and last updated on 2026-04-15.
A set of benchmark functions used to evaluate the Felis Catus Optimization (FCO) metaheuristic algorithm. The dataset includes results from experiments on the CEC 2005 and CEC 2017 benchmark suites and three real-world engineering design problems. It was created by Mohammad Salehi and last updated on April 15, 2026.
Counterfactual VLM Benchmark Data is a dataset payload for evaluating vision-language models. It was authored by JingyuSun and uploaded to Hugging Face on May 20, 2026. The dataset is intended to be used with an associated GitHub repository containing download and evaluation scripts.
UMI-VQA-8M is a large-scale visual question answering dataset built for UMI-style wrist-mounted fisheye observations. It contains 8 million visual question-answering samples and provides visual-language supervision for UMI observation scenarios. The dataset was created by TeleEmbodied and was last updated on the Hugging Face platform in June 2026.
prithivMLmods's dataset contains 27,048 English image-caption pairs, with images at 512x512 resolution. The data is derived from curated sources like blip3o-caption-mini-arrow and was last updated on May 17, 2026. It is designed for training and evaluating image-to-text models.
Yezhi Cui's study on figshare, last updated April 22, 2026, investigates the neural mechanisms of Mandarin tone sandhi perception. The dataset includes functional near-infrared spectroscopy (fNIRS) data and behavioral responses from 44 Vietnamese-speaking learners during a tone discrimination task. The data was collected to compare a gesture training group with a no-gesture control group.
MMS-VPR is a large-scale multimodal street-level visual place recognition dataset created by Yiwei-Ou. It comprises 110,529 images and 2,527 video clips with textual annotations, featuring day-night coverage and a 7-year temporal span in dense pedestrian-only environments. The dataset was last updated on HuggingFace on May 20, 2026.
Xuhong Nan published a study on figshare in April 2026 analyzing multimodal ultrasound data from 65 patients with type 2 diabetes mellitus and 27 control subjects. The dataset includes measurements of carotid intima-media thickness, blood flow velocities, wall shear stress, and pulse wave velocity. The study explores subclinical vascular changes associated with diabetes.
AbstractPhil's diffusion-pretrain-set-ft1 is a multi-source image-caption dataset assembled from seven upstream sources via a uniform ingest pipeline. It was built for the finetune-1 stage of the sd15-flow-lune model family but is applicable to any Stable Diffusion 1.x conditioning experiment. The dataset was last updated on May 22, 2026.
~1.51 million samples across eight splits comprise this multimodal reasoning dataset. It was created by RuoliuYang and last updated on May 25, 2026. The splits include text-based chain-of-thought reasoning, bounding box manipulations, and visual representations like depth maps.
ETCHR GRPO-10K is a dataset of 10,000 multimodal samples created by internlm for enhancing model editing capabilities. It contains five specific tasks: Fine-grained Perception, Chart Understanding, Maze Solving, Jigsaw Puzzle, and Spatial Understanding. Each sample includes an image to be edited and an editing instruction.
Raw evaluation metrics and execution telemetry logs from running the Mostly Basic Python Problems (MBPP) benchmark against the Qwen3 8B dense foundation model. The dataset documents zero-shot functional programming synthesis performance under standard local execution bounds. It was authored by ShahzebKhoso and last updated on May 29, 2026.
A 2026 protocol document for a randomized controlled trial investigating a novel acupuncture technique for Parkinson's disease. The study, authored by Wanqing Peng, involves 69 patients and uses multimodal MRI to assess neuroplasticity mechanisms alongside clinical symptom scales. The document is a 104.0 KB PDF published under a CC-BY-4.0 license.
Wanqing Peng's protocol document outlines a triple-arm randomized controlled trial investigating Qihuang needle therapy for Parkinson's disease. The trial, registered as ITMCTR2025000402, will enroll 69 patients to assess clinical efficacy and neuroplasticity via multimodal MRI. The document was last updated on 2026-04-13.
A clinical trial protocol for a triple-arm randomized controlled trial investigating Qihuang needle therapy for Parkinson's disease. The dataset includes clinical outcomes and multimodal MRI neuroplasticity markers from 69 patients. The protocol was authored by Wanqing Peng and uploaded to figshare in April 2026.
A dataset designed to strengthen multi-turn, interactive capabilities, including open-ended chat and precise instruction following. The chat subset uses human-written prompts from sources like lmarena, lmsys, and wildchat as seed prompts, with responses generated by GLM-5 and selected via pairwise comparisons using a reward model. It was authored by NVIDIA and last updated on the platform in June 2026.