✨Decouple to Generalize: Context-First Self-Evolving Learning for Data-Scarce Vision-Language Reasoning
📝 Summary:
DoGe is a framework that addresses data scarcity in vision-language models. It decouples context learning from problem solving, using a curriculum to improve reward signals and data diversity. This enhances generalization and performance.
🔹 Publication Date: Published on Dec 7
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.06835
• PDF: https://arxiv.org/pdf/2512.06835
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For more data science resources:
✓ https://t.iss.one/DataScienceT
#VisionLanguage #DataScarcity #MachineLearning #AIResearch #DeepLearning
📝 Summary:
DoGe is a framework that addresses data scarcity in vision-language models. It decouples context learning from problem solving, using a curriculum to improve reward signals and data diversity. This enhances generalization and performance.
🔹 Publication Date: Published on Dec 7
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.06835
• PDF: https://arxiv.org/pdf/2512.06835
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#VisionLanguage #DataScarcity #MachineLearning #AIResearch #DeepLearning
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