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[short] Visualization-of-Thought Elicits Spatial Reasoning in Large Language Models
Visualization-of-Thought (VoT) prompts enhance spatial reasoning in large language models (LLMs), outperforming multimodal models in tasks like navigation and tiling, resembling human cognitive processes.
https://arxiv.org/abs//2404.03622
YouTube: https://www.youtube.com/@ArxivPapers
TikTok: https://www.tiktok.com/@arxiv_papers
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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By Igor Melnyk
5
33 ratings
Visualization-of-Thought (VoT) prompts enhance spatial reasoning in large language models (LLMs), outperforming multimodal models in tasks like navigation and tiling, resembling human cognitive processes.
https://arxiv.org/abs//2404.03622
YouTube: https://www.youtube.com/@ArxivPapers
TikTok: https://www.tiktok.com/@arxiv_papers
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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