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R1-V is an initiative aimed at enhancing the generalization capabilities of Vision-Language Models (VLMs) through Reinforcement Learning in Visual Reasoning (RLVR). The project focuses on building a comprehensive framework that emphasizes algorithm enhancement, efficiency optimization, and task diversity to achieve general vision-language intelligence and visual/GUI agents. The team's long-term goal is to contribute impactful open-source research in this domain.
Features
- Reinforcement learning integration for visual reasoning
- Focus on algorithm enhancement
- Efficiency optimization strategies
- Diverse task handling capabilities
- Development of general vision-language intelligence
- Creation of visual/GUI agents
- Open-source research contributions
- Availability of training datasets like CLEVR-70k-Counting
- Collaborative team of researchers
Project Samples
Categories
Computer Vision LibrariesFollow R1-V
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