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This PR adds LLaVA-Plus, a significant advancement in multimodal AI that introduces:

  • First visual instruction dataset specifically for multimodal tool use
  • Novel approach to dynamic tool/skill integration in multimodal models
  • State-of-the-art performance across multiple benchmarks
  • Complete reproducibility with public code, data, and checkpoints

The resource includes:

  • Paper link and implementation details
  • Original analysis of technical significance
  • Code examples demonstrating core concepts
  • Proper categorization within the multimodal section

Related Links:

This PR adds LLaVA-Plus, a significant advancement in multimodal AI that introduces:
- First visual instruction dataset specifically for multimodal tool use
- Novel approach to dynamic tool/skill integration in multimodal models
- State-of-the-art performance across multiple benchmarks
- Complete reproducibility with public code, data, and checkpoints

The resource includes:
- Paper link and implementation details
- Original analysis of technical significance
- Code examples demonstrating core concepts
- Proper categorization within the multimodal section

Related Links:
- Paper: https://arxiv.org/abs/2311.05437
- Code: https://github.com/LLaVA-VL/LLaVA-Plus-Codebase
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