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

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References (45)

[1]

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.

[3]

Mitigating Modal Imbalance in Multimodal Reasoning

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 Models•Score: 8•View PDF ↗

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

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References (45)

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."

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

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References (45)

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."

Commercial Viability Breakdown

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