datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
SPaRC
SPaRC Dataset
Website • Solver • Generator
A grid-based puzzle dataset for benchmarking LLMs spatial reasoning capabilities.
Data Schema
Each record (JSON) includes:
id (string): unique puzzle identifier
difficulty_level (int) & difficulty_score (float)
grid_size: { "height": H, "width": W }
polyshapes: JSON string mapping shape IDs to binary grids
puzzle_array: 2D array with cell codes (e.g., S, E, +, P-O-112)
solution_count (int) and solutions list (with… See the full description on the dataset page: https://huggingface.co/datasets/lkaesberg/SPaRC.benchmark_DEMAND_noise
benchmark_DEMAND_noise
This dataset is a segmented subset derived from DEMAND: Diverse Environments Multichannel Acoustic Noise Database.
It is prepared for the SPARCO noise ablation benchmark. The intended use is to provide fixed 4-second environmental noise segments for:
AUROC-based SAE noise-related feature selection
binary noise-presence scorer training
scorer threshold calibration
final held-out benchmark evaluation
Source
Original source:
DEMAND: Diverse… See the full description on the dataset page: https://huggingface.co/datasets/SPARCO-project/benchmark_DEMAND_noise.SPARC-VQA
SPARC VQA
SPARC VQA is the generated spatial VQA training dataset used in the SPARC Qwen3.5 model releases. Each example embeds its image bytes and includes a question, answer, task type, target type, source dataset identifier, split, and JSON metadata.
Raw unfiltered corpus: https://huggingface.co/datasets/irl-kit/SPARC-VQA-Raw
Ready-to-train split
Use train_filtered_t097_mpo700.parquet for SPARC-only training. This is the processed, release-ready dataset: it… See the full description on the dataset page: https://huggingface.co/datasets/irl-kit/SPARC-VQA.sparc
Dataset Card for SParC
SParC is a context-dependant multi-turn version of the Spider task 1.0.
This dataset provides a chat-bot oriented test set for text-to-sql problems. Additional details may be obtained in the paper:
https://arxiv.org/abs/1906.02285
Paper Abstract
We present SParC, a dataset for cross-domainSemanticParsing inContext that consists of 4,298 coherent question sequences (12k+ individual questions annotated with SQL queries). It is obtained from… See the full description on the dataset page: https://huggingface.co/datasets/aherntech/sparc.stocks-SPARC-1D-candlesSPARC
SPaRC Dataset
Website • Solver • Generator
A grid-based puzzle dataset for benchmarking LLMs spatial reasoning capabilities.
Data Schema
Each record (JSON) includes:
id (string): unique puzzle identifier
difficulty_level (int) & difficulty_score (float)
grid_size: { "height": H, "width": W }
polyshapes: JSON string mapping shape IDs to binary grids
puzzle_array: 2D array with cell codes (e.g., S, E, +, P-O-112)
solution_count (int) and solutions list (with index… See the full description on the dataset page: https://huggingface.co/datasets/jamilalthani1/SPARC.benchmark-noise_ablation
benchmark-noise_ablation
This dataset contains fixed-length noisy speech mixtures generated from LibriSpeech test-clean clean speech and two interference types:
50% DEMAND environmental background noise
50% generated white noise
The dataset is intended for SPARCO noise ablation experiments, including:
AUROC-based SAE noise-related feature selection
binary noise-presence scorer training
scorer threshold calibration
final held-out benchmark evaluation
Sources
Clean… See the full description on the dataset page: https://huggingface.co/datasets/SPARCO-project/benchmark-noise_ablation.SParC@InProceedings{Yu&al.19,
title = {SParC: Cross-Domain Semantic Parsing in Context},
author = {Tao Yu and Rui Zhang and Michihiro Yasunaga and Yi Chern Tan and Xi Victoria Lin and Suyi Li and Heyang Er, Irene Li and Bo Pang and Tao Chen and Emily Ji and Shreya Dixit and David Proctor and Sungrok Shim and Jonathan Kraft, Vincent Zhang and Caiming Xiong and Richard Socher and Dragomir Radev},
booktitle = {Proceedings of the 57th Annual Meeting of the Association for Computational… See the full description on the dataset page: https://huggingface.co/datasets/jellyChiru/SParC.sparc-rotation-curvesSQL_SparC_Dataset_With_Schema
Dataset Card for "SQL_SparC_Dataset_With_Schema"
More Information needed
benchmark-pitchSPARC-VQA-Raw
SPARC VQA Raw
This repository contains the unfiltered SPARC VQA corpus: 838,211 embedded-image training examples in train.parquet (33.20 GB). Each example contains an image, question, answer, task metadata, source identifier, and annotation metadata including selected_start_score.
Ready-to-train version
For the exact processed SPARC subset used by the released Qwen3.5 models, download train_filtered_t097_mpo700.parquet from irl-kit/SPARC-VQA. It contains 284,909… See the full description on the dataset page: https://huggingface.co/datasets/irl-kit/SPARC-VQA-Raw.sparc-droid-annotations
SPARC DROID annotations
SPARC annotations for DROID. This repository contains annotations only. It does not redistribute DROID
images, videos, actions, or robot states; obtain the source dataset separately.
Each JSONL row describes one interaction subtask from one camera view. Dense
arrays live in HDF5 sidecars referenced by that row. All coordinates, masks,
and frame indices refer to the original uncropped, unresized DROID camera
frames.
Release contents… See the full description on the dataset page: https://huggingface.co/datasets/irl-kit/sparc-droid-annotations.sparcspar-concepts
SPAR steering concepts
Contrastive texts for building steering directions, used by the SPAR project for the GLP steering evals and for
training and evaluating the cold-diffusion model. A concept is a set of positive texts (target=1, concept
present) and negative texts (target=0, concept absent); its steering direction is the diff-of-means of a model's
activations on the two classes, exactly as in the GLP sentiment eval.
Configs
config
rows
content
texts… See the full description on the dataset page: https://huggingface.co/datasets/basta/spar-concepts.benchmark-sisdrbenchmark-genderbenchmark-speech-f0benchmark-instrumentsparc-llama2benchmark-eventbenchmark-timesparc-galaxiesspar-cotsparc_projectsparc