datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ParseBench
ParseBench
Quick links: [🌐 Website] [📜 Paper] [💻 Code]
ParseBench is a benchmark for evaluating document parsing systems on real-world enterprise documents, with the following characteristics:
Multi-dimensional evaluation. The benchmark is stratified into five capability dimensions — tables, charts, content faithfulness, semantic formatting, and visual grounding — each with task-specific metrics designed to capture what agentic workflows depend on.
Real-world enterprise… See the full description on the dataset page: https://huggingface.co/datasets/llamaindex/ParseBench.ParseBench
ParseBench
Quick links: [🌐 Website] [📜 Paper] [💻 Code]
ParseBench is a benchmark for evaluating document parsing systems on real-world enterprise documents, with the following characteristics:
Multi-dimensional evaluation. The benchmark is stratified into five capability dimensions — tables, charts, content faithfulness, semantic formatting, and visual grounding — each with task-specific metrics designed to capture what agentic workflows depend on.
Real-world enterprise… See the full description on the dataset page: https://huggingface.co/datasets/Yoongls/ParseBench.ParseBench
ParseBench
Quick links: [🌐 Website] [📜 Paper] [💻 Code]
ParseBench is a benchmark for evaluating document parsing systems on real-world enterprise documents, with the following characteristics:
Multi-dimensional evaluation. The benchmark is stratified into five capability dimensions — tables, charts, content faithfulness, semantic formatting, and visual grounding — each with task-specific metrics designed to capture what agentic workflows depend on.
Real-world enterprise… See the full description on the dataset page: https://huggingface.co/datasets/huggingworld/ParseBench.ParseBench
ParseBench
Quick links: [🌐 Website] [📜 Paper] [💻 Code]
ParseBench is a benchmark for evaluating document parsing systems on real-world enterprise documents, with the following characteristics:
Multi-dimensional evaluation. The benchmark is stratified into five capability dimensions — tables, charts, content faithfulness, semantic formatting, and visual grounding — each with task-specific metrics designed to capture what agentic workflows depend on.
Real-world enterprise… See the full description on the dataset page: https://huggingface.co/datasets/matthew-l-leidos/ParseBench.ParseBench_test
ParseBench
Quick links: [🌐 Website] [📜 Paper] [💻 Code]
ParseBench is a benchmark for evaluating document parsing systems on real-world enterprise documents, with the following characteristics:
Multi-dimensional evaluation. The benchmark is stratified into five capability dimensions — tables, charts, content faithfulness, semantic formatting, and visual grounding — each with task-specific metrics designed to capture what agentic workflows depend on.
Real-world enterprise… See the full description on the dataset page: https://huggingface.co/datasets/kramp/ParseBench_test.chart-parse-bench
ChartParse-Bench
58 synthetic charts whose exact values were written before the pixels existed.
Every gate in chart extraction measures self-consistency: redraw the extraction, check it
lands on the same ink, call it verified. That passes a series traced confidently off the
wrong axis. Because each chart here ships the array it was drawn from, the question stops
being is this answer plausible and becomes is this answer right.
Contents
family
charts
series… See the full description on the dataset page: https://huggingface.co/datasets/Unsiloed/chart-parse-bench.