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README.md
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- split: test
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path: data/test-*
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- split: test
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path: data/test-*
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---
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---
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license: mit
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datasets:
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- Yuting6/geoqa-r1v-augmentation
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- Yuting6/math-8k-augmentation
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- Yuting6/m3cot-augmentation
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- Yuting6/TQA-augmentation
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- Yuting6/Geo3k-augmentation
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- Yuting6/geoqa-r1v-noise
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- Yuting6/geoqa-r1v-crop
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- Yuting6/geoqa-r1v-blur
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- Yuting6/geoqa-r1v-8k-rotated
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- Yuting6/geoqa-r1v-8k-mixup
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base_model:
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- Qwen/Qwen2.5-VL-7B-Instruct
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---
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# Vision Matters: Simple Visual Perturbations Can Boost Multimodal Math Reasoning
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## Paper Title and Link
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The model was presented in the paper [Vision Matters: Simple Visual Perturbations Can Boost Multimodal Math Reasoning](https://arxiv.org/abs/2506.09736). You can also find the paper on arXiv: [Vision Matters: Simple Visual Perturbations Can Boost Multimodal Math Reasoning (arXiv:2506.09736)](https://arxiv.org/abs/2506.09736)
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## Paper Abstract
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Vision-Matters is a simple visual perturbation framework that can be easily integrated into existing post-training pipelines including SFT, DPO, and GRPO. Our findings highlight the critical role of visual perturbation: better reasoning begins with better seeing.
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* 🐙 **GitHub Repo:** [YutingLi0606/Vision-Matters](https://github.com/YutingLi0606/Vision-Matters)
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* 💾 **Dataset:** [Yuting6/vision-matters on Hugging Face](https://huggingface.co/collections/Yuting6/vision-matters-684801dd1879d3e639a930d1)
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