"VoT" Gives LLMs Spacial Reasoning AND Open-Source "Large Action Model"

1. Spatial reasoning is crucial for large language models.

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Large language models historically lacked spatial reasoning abilities, hindering progress towards AGI. The paper demonstrates the feasibility of imbuing llms with spatial reasoning capabilities.

• Spatial reasoning involves visualizing relationships in a 3D or 2D environment.
• Yan LeCun highlighted spatial reasoning as a critical missing feature for large language models.
• The paper proves that large language models can indeed possess spatial reasoning.

2. Visualization of thought enhances large language models.

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Utilizing visualization of thought prompts improves llms' performance significantly, especially in tasks requiring spatial awareness like navigation and tiling.

• Visualizing reasoning steps aids llms in spatial reasoning tasks.
• VOT prompting method augments llms with a visual spatial sketch pad.
• Zero-shot prompting enhances llms' spatial reasoning capabilities.

3. Open-source large action model empowers human-computer interaction.

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The PiWin Assistant, an open-source large action model, enables controlling human interfaces solely through natural language commands, showcasing the potential of advanced llms.

• PiWin Assistant exemplifies the practical application of advanced llms in real-world tasks.
• The model demonstrates controlling a Windows environment using natural language instructions.
• This innovation opens avenues for seamless human-AI interaction.

4. AI can be instructed to perform specific tasks.

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Users can instruct AI to create social media posts, demonstrating the AI's ability to follow detailed instructions.

• AI can be directed to perform tasks like making a new post on Twitter with specific content.
• The AI iterates on prompts automatically and provides updates on its current understanding.
• Visualizations show each step of the AI's process, enhancing transparency.

5. AI can generate a sequence of actions to achieve tasks.

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AI can generate a series of actions, such as clicking on browser elements and entering specific websites, to accomplish tasks.

• The AI can locate elements on a webpage, enter URLs, and perform actions step by step.
• It provides a detailed set of instructions for each action required to complete a task.
• The AI's ability to follow a sequence of actions showcases its practical application in task completion.