Mitigating spatial hallucination in large language models for path planning via prompt engineering
Abstract Spatial reasoning in Large Language Models (LLMs) serves as a foundation for embodied intelligence. However, even in simple maze environments, LLMs often struggle to plan correct paths due to hallucination issues. To address this, we propose S2ERS, an LLM-based technique that integrates ent...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-03-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-93601-5 |
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