Dataset · Hugging Face

inclusionAI/ZwZ-RL-VQA

Name: ZwZ-RL-VQA
Creator: inclusionAI
License: apache-2.0
Keywords: language:en, license:apache-2.0, size_categories:100K<n<1M, format:parquet, modality:text, library:datasets, library:dask, library:polars, library:mlcroissant, arxiv:2602.11858, region:us, multimodal, vision-language-model, fine-grained-perception, vqa

ZwZ-RL-VQA: Region-to-Image Distilled Training Data for Fine-Grained Perception This synthetic dataset is generated via Region-to-Image Distillation (R2I) for training multimodal large language models (MLLMs) on fine-grained perception tasks without test-time tool use. 📖 Overview The Zooming without Zooming (ZwZ) method transforms "zooming" from an inference-time tool into a training-time primitive: Zoom-in Synthesis: Strong teacher models (Qwen3-VL-235B… See the full description on the dataset page: https://huggingface.co/datasets/inclusionAI/ZwZ-RL-VQA.

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Author / organization	inclusionAI
License (as declared)	apache-2.0
Downloads	2.6K (as reported by Hugging Face)
Likes	17
Created	12 February 2026
Last updated at source	28 May 2026

multimodalvision-language-modelfine-grained-perceptionvqaregion-to-image-distillation

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Connected in the knowledge graph

inclusionAI/ZwZ-8BModel · used to train
mradermacher/ZwZ-8B-i1-GGUFModel · used to train
mradermacher/ZwZ-4B-GGUFModel · used to train
mradermacher/ZwZ-8B-heretic-i1-GGUFModel · used to train
mradermacher/ZwZ-4B-i1-GGUFModel · used to train
mradermacher/ZwZ-8B-heretic-GGUFModel · used to train
mradermacher/ZwZ-8B-PaperWitch-heresy-i1-GGUFModel · used to train
inclusionAI/ZwZ-4B-GGUFModel · used to train
inclusionAI/ZwZ-7BModel · used to train
mradermacher/ZwZ-8B-GGUFModel · used to train
mradermacher/ZwZ-7B-i1-GGUFModel · used to train
inclusionAI/ZwZ-4BModel · used to train
mradermacher/ZwZ-8B-PaperWitch-heresy-GGUFModel · used to train
mradermacher/ZwZ-7B-GGUFModel · used to train
inclusionAI/ZwZ-2BModel · used to train
inclusionAI/ZwZ-2B-GGUFModel · used to train

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16 Oct 2026 Description: ZwZ-RL-VQA: Region-to-Image Distilled Training Data for Fine-Grained Perception This synthetic dataset is generated via Region-to-Image Distillation (R2I) for training multimodal large language models (MLLMs) on fine-grained perception task → ZwZ-RL-VQA: Region-to-Image Distilled Training Data for Fine-Grained Perception This synthetic dataset is generated via Region-to-Image Distillation (R2I) for training multimodal large language models (MLLMs) on fine-grained perception task

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