Does the Question Really Matter? Training-Free Data Selection for Vision-Language SFT

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Why Less is More (Sometimes): A Theory of Data Curation
2025Elvis Dohmatob, Mohammad Pezeshki et al.
[2]
CoIDO: Efficient Data Selection for Visual Instruction Tuning via Coupled Importance-Diversity Optimization
2025Yichen Yan, Ming Zhong et al.
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Mitigating Modal Imbalance in Multimodal Reasoning
2025C. Wu, Neil Kale et al.
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Data Selection for Fine-tuning Vision Language Models via Cross Modal Alignment Trajectories
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2025Yiwei Ma, Guohai Xu et al.
[9]
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2025Mong Yuan Sim, Wei Emma Zhang et al.
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Founder's Pitch

"CVS is a training-free data selection method that enhances vision-language model performance by identifying samples requiring genuine cross-modal reasoning."

Vision-Language ModelsScore: 8View PDF ↗

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0-10 scale

High Potential

2/4 signals

5

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2/4 signals

5

Series A Potential

3/4 signals

7.5

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