Structured Maps for Landmark-Based Route Instructions with LLMs

The paper introduces a structured text representation using SVG to encode map geometry for landmark-based route instruction generation. It shows that large language models can use this representation to select landmarks at turns and near destinations, performing as well or better than image-based inputs. Fine‑tuning smaller local LLMs further improves accuracy, demonstrating the efficiency of structured text for spatial reasoning in navigation.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

• llms
• fine-tuning