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A new paper introduces Visual CoT, a new approach that enhances multi-modal large language models with visual chain-of-thought reasoning capabilities. This allows language models to dynamically identify and focus on specific regions within images that are most relevant for answering questions, mimicking human-like efficient visual reasoning.
A new paper introduces Visual CoT, a new approach that enhances multi-modal large language models with visual chain-of-thought reasoning capabilities. This allows language models to dynamically identify and focus on specific regions within images that are most relevant for answering questions, mimicking human-like efficient visual reasoning.
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Keypoints:
Keypoints:
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* Introduces the 373k Visual CoT dataset with bounding box annotations highlighting essential image regions
* Introduces the 373k Visual CoT dataset with bounding box annotations highlighting essential image regions
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* Proposes a multi-turn pipeline for focusing on relevant visual inputs
* Proposes a multi-turn pipeline for focusing on relevant visual inputs
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* Achieves strong results on multi-modal benchmarks 
* Achieves strong results on multi-modal benchmarks 
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Paper: 
Paper: 
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https://huggingface.co/papers/2403.16999
paper
2403.16999
https://huggingface.co/papers/2403.16999
Visual CoT: Unleashing Chain-of-Thought Reasoning in Multi-Modal
  Language Models (2403.16999)
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Code, data and other resources: 
Code, data and other resources: 
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https://github.com/deepcs233/Visual-CoT
https://github.com/deepcs233/Visual-CoT
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Congrats to the authors for their work!
Congrats to the authors for their work!
A new paper introduces Visual CoT, a new approach that enhances multi-modal large language models with visual chain-of-thought reasoning capabilities. This allows language models to dynamically identify and focus on specific regions within images that are most relevant for answering questions, mimicking human-like efficient visual reasoning.

Keypoints:
* Introduces the 373k Visual CoT dataset with bounding box annotations highlighting essential image regions
* Proposes a multi-turn pipeline for focusing on relevant visual inputs
* Achieves strong results on multi-modal benchmarks 

Paper: https://huggingface.co/papers/2403.16999
Code, data and other resources: https://github.com/deepcs233/Visual-CoT

Congrats to the authors for their work!
❤️
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