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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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