datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
SDG-30K
SDG-30K — Structured Defect Grounding Dataset
A 30,000-image dataset for structured defect grounding in text-to-image
generations. Each image is annotated with bounding-box-level defects, where
each defect carries:
a category (artifact for visual flaws / misalignment for caption-image
mismatches),
a natural-language description, and
a chain-of-thought reasoning trace.
This is the public release accompanying the NeurIPS 2026 anonymous submission
"SDG: Structured Defect… See the full description on the dataset page: https://huggingface.co/datasets/P1n3/SDG-30K.OpenGameArt-CC-BY-SA-3.0
Dataset Card for OpenGameArt-CC-BY-SA-3.0
Dataset Summary
This dataset contains game artwork assets collected from OpenGameArt.org that are specifically released under the Creative Commons Attribution-ShareAlike 3.0 Unported (CC-BY-SA-3.0) license. The dataset includes various types of game assets such as 2D art, 3D art, concept art, music, sound effects, textures, and documents along with their associated metadata.
Languages
The dataset is primarily… See the full description on the dataset page: https://huggingface.co/datasets/nyuuzyou/OpenGameArt-CC-BY-SA-3.0.OpenGameArt-OGA-BY-3.0
Dataset Card for OpenGameArt-OGA-BY-3.0
Dataset Summary
This dataset contains game artwork assets collected from OpenGameArt.org that are specifically released under the OpenGameArt Attribution (OGA-BY-3.0) license. The dataset includes various types of game assets such as 2D art, 3D art, concept art, music, sound effects, textures, and associated metadata.
Languages
The dataset is primarily monolingual:
English (en): All asset descriptions and metadata are in… See the full description on the dataset page: https://huggingface.co/datasets/nyuuzyou/OpenGameArt-OGA-BY-3.0.OpenGameArt-CC-BY-3.0
Dataset Card for OpenGameArt-CC-BY-3.0
Dataset Summary
This dataset contains game artwork assets collected from OpenGameArt.org that are specifically released under the Creative Commons Attribution 3.0 (CC-BY-3.0) license. The dataset includes various types of game assets such as 2D art, 3D art, concept art, music, sound effects, textures, and documents along with their associated metadata.
Languages
The dataset is primarily monolingual:
English (en): All… See the full description on the dataset page: https://huggingface.co/datasets/nyuuzyou/OpenGameArt-CC-BY-3.0.OpenGameArt-GPL-3.0
Dataset Card for OpenGameArt-GPL-3.0
Dataset Summary
This dataset contains game artwork assets collected from OpenGameArt.org that are specifically released under the GNU General Public License version 3.0 (GPL-3.0). The dataset includes various types of game assets such as 2D art, 3D art, concept art, music, sound effects, and textures along with their associated metadata.
Languages
The dataset is primarily monolingual:
English (en): All asset descriptions… See the full description on the dataset page: https://huggingface.co/datasets/nyuuzyou/OpenGameArt-GPL-3.0.OpenGameArt-GPL-3.0
Dataset Card for OpenGameArt-GPL-3.0
Dataset Summary
This dataset contains game artwork assets collected from OpenGameArt.org that are specifically released under the GNU General Public License version 3.0 (GPL-3.0). The dataset includes various types of game assets such as 2D art, 3D art, concept art, music, sound effects, and textures along with their associated metadata.
Languages
The dataset is primarily monolingual:
English (en): All asset descriptions… See the full description on the dataset page: https://huggingface.co/datasets/irfankabir02/OpenGameArt-GPL-3.0.figmirror-unified
Unified FigMirror Dataset
Canonical release with 550 samples.
dataset_augmentation: 500
paper_derivative: 50
paper_derivative verified_pass: 50
Data unit:
One row in data/train.jsonl is one task / one data point.
Asset files under assets/ are supporting files, not separate data points.
Semantic task families:
chart_style_augmentation: input is a reference/source chart; output is an augmented chart.
paper_figure_reproduction: input is a paper figure reference; output is a… See the full description on the dataset page: https://huggingface.co/datasets/zcahjl3/figmirror-unified.MixedWM38-VQA
Wafer VQA Dataset
Overview
Wafer VQA Dataset is a multimodal benchmark for wafer map understanding, visual question answering, and defect reasoning. It is built on top of the MixedWM38 wafer-map collection and organized into two annotation styles:
tuple_generation: one multi-question response per image, intended for GRPO or other sequence-level optimization settings
stepwise_reasoning: one stepwise dialogue per image, intended for supervised fine-tuning… See the full description on the dataset page: https://huggingface.co/datasets/wafervqaanon/MixedWM38-VQA.