Generalization in LLM Problem Solving: The Case of the Shortest Path
Researchers created a controlled synthetic environment using shortest-path planning to isolate factors affecting LLM generalization. Models showed strong spatial transfer to unseen maps but consistently failed when scaling to longer horizons due to recursive instability, revealing a key limitation in systematic problem-solving.
MentionsLanguage Models · Shortest-Path Planning · Generalization
Read full story at arXiv cs.LG →(arxiv.org)
Modelwire summarizes — we don’t republish. The full article lives on arxiv.org. If you’re a publisher and want a different summarization policy for your work, see our takedown page.