datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
MAPBench-V2For more details, please check our project page.
Paper: https://arxiv.org/abs/2601.05432
Repository: https://github.com/AMAP-ML/Thinking-with-Map
easyr1-agent-grounding-dataOmniParsingBench
🤗 Model | 📑 Technical Report | 💻 GitHub
OmniParsingBench is a comprehensive, large-scale, and high-quality evaluation corpus designed to rigorously evaluate the unified parsing capabilities of Multimodal Large Language Models (MLLMs) across diverse modalities.
Unlike traditional single-task benchmarks, OmniParsingBench assesses the full spectrum of parsing performance—from fundamental signal detection to complex semantic reasoning—across six primary domains: Document… See the full description on the dataset page: https://huggingface.co/datasets/Logics-MLLM/OmniParsingBench.seeclick-web-commercial-mlx
SeeClick Web Commercial Dataset (MLX-VLM Format)
Commercial-use friendly GUI grounding dataset from SeeClick Web data.
Apache 2.0 licensed - safe for commercial applications.
Dataset Description
This dataset contains ~20k examples for training Vision-Language Models to predict
click coordinates given a screenshot and instruction. Derived from SeeClick Web
crawled data (Apache 2.0).
Key Features
License: Apache 2.0 (commercial use allowed)
Format: MLX-VLM… See the full description on the dataset page: https://huggingface.co/datasets/pierretokns/seeclick-web-commercial-mlx.MAPBench-V1For more details, please check our project page.
Paper: https://arxiv.org/abs/2601.05432
Repository: https://github.com/AMAP-ML/Thinking-with-Map
MindTopo
MindTopo
Multimodal benchmark probing whether foundation models reason about topological structure — connectivity, enclosure, knottedness, ordering, separation — rather than relying on superficial visual cues. 8,910 procedurally generated examples across 13 environments / 5 categories.
This repository revision contains only the question / metadata jsonl files. Rendered images for the perception environments are distributed separately (see project page) due to size.… See the full description on the dataset page: https://huggingface.co/datasets/MLL-Lab/MindTopo.ml-design-doc-reviewer-data
ml-system-design/ml-design-doc-reviewer-data (v1.0.0)
Evaluation artifacts for the ML Design Doc Reviewer project.
Layout
Path
Description
manifest/sample_manifest.csv
Stratified 100-case sample manifest
manifest/error_topology.csv
Controlled error taxonomy for flawed docs
raw/
Raw markdown exports, metadata sidecars, OCR image blocks
raw/images/
Downloaded article images
normalized/
Canonical 14-section ML design documents
flawed/
Normalized… See the full description on the dataset page: https://huggingface.co/datasets/ml-system-design/ml-design-doc-reviewer-data.