datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
H3-IR
H3-IR
H3-IR contains privacy-reviewed prompt/Context-IR pairs for training H3 prompt
enhancers. The public export is fail-closed: a row is included only when its
text, annotation, and every referenced media asset pass both privacy and
redistribution-rights gates.
Splits
Split
Rows
train
1110
validation
81
total
1191
Privacy Review
All source rows and unique visual assets were reviewed with gpt-5.6-sol at
reasoning_effort=xhigh… See the full description on the dataset page: https://huggingface.co/datasets/StellarVoyager/H3-IR.STELAR-topo_vision_reasoning_SFT_50k
Stellar-Neuron/STELAR-topo_vision_reasoning_SFT_50k
[Paper] [HF Collection] [Project Page]
The dataset was released as part of STELAR-VISION: Self-Topology-Aware Efficient Learning for Aligned Reasoning in Vision. STELAR is a more accurate, faster and greener intelligent system for Vision Language Reasoning.
Contact: chenli4@andrew.cmu.edu
Dataset Summary
This dataset was created by STELAR TopoAug from two base datasets: Math-V and VLM_S2H. Each question includes… See the full description on the dataset page: https://huggingface.co/datasets/Stellar-Neuron/STELAR-topo_vision_reasoning_SFT_50k.STELAR-topo_vision_reasoning_100k
Stellar-Neuron/STELAR-topo_vision_reasoning_100k
[Paper] [HF Collection] [Project Page]
The dataset was released as part of STELAR-VISION: Self-Topology-Aware Efficient Learning for Aligned Reasoning in Vision. STELAR is a more accurate, faster and greener intelligent system for Vision Language Reasoning.
Contact: chenli4@andrew.cmu.edu
Dataset Summary
This dataset was created by STELAR TopoAug from two base datasets: Math-V and VLM_S2H. Each question includes responses… See the full description on the dataset page: https://huggingface.co/datasets/Stellar-Neuron/STELAR-topo_vision_reasoning_100k.STELAR-topo_vision_reasoning_preference_123k
Stellar-Neuron/STELAR-topo_vision_reasoning_preference_123k
[Paper] [HF Collection] [Project Page]
The dataset was released as part of STELAR-VISION: Self-Topology-Aware Efficient Learning for Aligned Reasoning in Vision. STELAR is a more accurate, faster and greener intelligent system for Vision Language Reasoning.
Contact: chenli4@andrew.cmu.edu
Dataset Summary
This dataset was created by STELAR TopoAug from two base datasets: Math-V and VLM_S2H.
Each question includes… See the full description on the dataset page: https://huggingface.co/datasets/Stellar-Neuron/STELAR-topo_vision_reasoning_preference_123k.FoldPlanet-500
FoldPlanet-500折叠星球
衣物折叠In-the-wild Human数据集
Version: 1.0
Author: 上海星际硅途技术有限公司
Date: 2025-10-24
公司介绍（Company Introduction）
上海星际硅途技术有限公司，成立于2025年4月，2025年9月入驻上海人形机器人孵化器。
我们是一家具身智能数据解决方案服务商，致力于通过“动作捕捉+视觉感知+语义标注”的多模态技术，进行“in-the-wild”场景下的“Human Data”采集，建立通专融合、覆盖千行百业的数据生态，推动具身智能数据行业宽度和深度的发展，促进具身智能大模型的快速迭代。
数据集简介（Dataset Overview）
专为具身智能人形机器人训练而设计的，高质量、结构化、可学习的真实泛化场景叠衣动作数据集。
它旨在帮助模型学习人类的行为逻辑、操作方式、物体交互特征以及任务理解能力。… See the full description on the dataset page: https://huggingface.co/datasets/stellarnexrobotics/FoldPlanet-500.stellar-classification-eda
Stellar Classification: Can we tell what's in space from telescope data?
Dataset Overview
I chose the Stellar Classification Dataset (SDSS17) from Kaggle, based on real data from the Sloan Digital Sky Survey. It contains 100,000 observations of celestial objects with 18 columns, mostly numeric measurements like light filters, sky coordinates, and redshift.
Main question: Can we classify whether a celestial object is a Star, Galaxy, or Quasar just from the numbers the… See the full description on the dataset page: https://huggingface.co/datasets/idoyaaran/stellar-classification-eda.