datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
TextVQA_GT_bbox
TextVQA validation set with grounding truth bounding box
The dataset used in the paper MLLMs Know Where to Look: Training-free Perception of Small Visual Details with Multimodal LLMs for studying MLLMs' attention patterns.
The dataset is sourced from TextVQA and annotated manually with ground-truth bounding boxes.
We consider questions with a single area of interest in the image so that 4370 out of 5000 samples are kept.
Citation
If you find our paper and code useful… See the full description on the dataset page: https://huggingface.co/datasets/jrzhang/TextVQA_GT_bbox.sat-bbox-metadata-sft-v1
Dataset Summary
NuTonic/sat-bbox-metadata-sft-v1 is a metadata-first, procedural VLM SFT dataset built from an existing “sat-bbox” style dataset tree (Sentinel‑2 chips + per-tile JSON metadata sidecars, optionally paired Mapbox stills).
The goal is to create high-signal, production-shaped supervision for multimodal chat models:
Captioning for satellite chips
Grounding (bounding boxes in normalized coordinates) for land-cover regions
Class-focused captions and absence checks for… See the full description on the dataset page: https://huggingface.co/datasets/NuTonic/sat-bbox-metadata-sft-v1.