✨SIMS-V: Simulated Instruction-Tuning for Spatial Video Understanding
📝 Summary:
SIMS-V uses 3D simulators to generate diverse spatial video training data. This efficiently trains multimodal language models, overcoming real-world data bottlenecks. A 7B model trained on this simulated data significantly outperforms larger baselines on real-world spatial reasoning tasks.
🔹 Publication Date: Published on Nov 6
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.04668
• PDF: https://arxiv.org/pdf/2511.04668
• Github: https://ellisbrown.github.io/sims-v/
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For more data science resources:
✓ https://t.iss.one/DataScienceT
#SpatialAI #MultimodalLLM #SimulatedData #ComputerVision #DeepLearning
📝 Summary:
SIMS-V uses 3D simulators to generate diverse spatial video training data. This efficiently trains multimodal language models, overcoming real-world data bottlenecks. A 7B model trained on this simulated data significantly outperforms larger baselines on real-world spatial reasoning tasks.
🔹 Publication Date: Published on Nov 6
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.04668
• PDF: https://arxiv.org/pdf/2511.04668
• Github: https://ellisbrown.github.io/sims-v/
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#SpatialAI #MultimodalLLM #SimulatedData #ComputerVision #DeepLearning