Experiments reveal that topological cues robustly support LLM navigation planning while incorrect semantic cues derail it, with linguistic format effects varying by model size and compression.
Can llm graph reasoning generalize beyond pattern memorization?arXiv preprint arXiv:2406.15992
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LLMs show strong spatial generalization to unseen maps in shortest-path tasks but fail length scaling due to recursive instability, with data coverage setting hard limits.
A neuro-symbolic system pairing LLMs for symbolic reasoning with neural delta controllers for execution delivers over 70% step reduction and up to 8.83x speedup in language-guided planar object manipulation while remaining robust to LLM quality.
citing papers explorer
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The Sword, Shield, and Achilles' Heel: Characterizing the Linguistic Inductive Bias of Large Language Models for Spatial Reasoning in Navigation Planning
Experiments reveal that topological cues robustly support LLM navigation planning while incorrect semantic cues derail it, with linguistic format effects varying by model size and compression.
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Generalization in LLM Problem Solving: The Case of the Shortest Path
LLMs show strong spatial generalization to unseen maps in shortest-path tasks but fail length scaling due to recursive instability, with data coverage setting hard limits.
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Neuro-Symbolic Control with Large Language Models for Language-Guided Spatial Tasks
A neuro-symbolic system pairing LLMs for symbolic reasoning with neural delta controllers for execution delivers over 70% step reduction and up to 8.83x speedup in language-guided planar object manipulation while remaining robust to LLM quality.