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@@ -7,13 +7,13 @@ license: apache-2.0
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  # Model Card for SpaceLLaVA
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- **SpaceLLaVA** uses LoRA to fine-tune [LLaVA](https://github.com/haotian-liu/LLaVA/tree/main) on a dataset designed with [VQASynth](https://github.com/remyxai/VQASynth/tree/main) to enhance spatial reasoning as in [SpatialVLM](https://spatial-vlm.github.io/)
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  ## Model Details
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  ### Model Description
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- This model uses data synthesis techniques and publically available models to reproduce the work described in SpatialVLM to enhance the spatial reasoning of multimodal models.
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  With a pipeline of expert models, we can infer spatial relationships between objects in a scene to create VQA dataset for spatial reasoning.
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  Use this model to query spatial relationships between objects in a scene.
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  ## Citation
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-
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  @article{chen2024spatialvlm,
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  title = {SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities},
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  author = {Chen, Boyuan and Xu, Zhuo and Kirmani, Sean and Ichter, Brian and Driess, Danny and Florence, Pete and Sadigh, Dorsa and Guibas, Leonidas and Xia, Fei},
@@ -42,8 +42,9 @@ Use this model to query spatial relationships between objects in a scene.
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  }
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  @misc{liu2023llava,
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- title={Visual Instruction Tuning},
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  author={Liu, Haotian and Li, Chunyuan and Wu, Qingyang and Lee, Yong Jae},
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  publisher={NeurIPS},
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  year={2023},
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  }
 
 
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  # Model Card for SpaceLLaVA
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+ **SpaceLLaVA** uses LoRA to fine-tune [LLaVA](https://github.com/haotian-liu/LLaVA/tree/main) on a dataset designed with [VQASynth](https://github.com/remyxai/VQASynth/tree/main) to enhance spatial reasoning as in [SpatialVLM](https://spatial-vlm.github.io/)
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  ## Model Details
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  ### Model Description
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+ This model uses data synthesis techniques and publically available models to reproduce the work described in SpatialVLM to enhance the spatial reasoning of multimodal models.
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  With a pipeline of expert models, we can infer spatial relationships between objects in a scene to create VQA dataset for spatial reasoning.
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  Use this model to query spatial relationships between objects in a scene.
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  ## Citation
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+ ```
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  @article{chen2024spatialvlm,
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  title = {SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities},
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  author = {Chen, Boyuan and Xu, Zhuo and Kirmani, Sean and Ichter, Brian and Driess, Danny and Florence, Pete and Sadigh, Dorsa and Guibas, Leonidas and Xia, Fei},
 
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  }
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  @misc{liu2023llava,
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+ title={Visual Instruction Tuning},
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  author={Liu, Haotian and Li, Chunyuan and Wu, Qingyang and Lee, Yong Jae},
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  publisher={NeurIPS},
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  year={2023},
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  }
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+ ```