Can LLMs Prove Robotic Path Planning Optimality? A Benchmark for Research-Level Algorithm Verification

Abstract

This work introduces a benchmark for evaluating whether large language models can produce research-level approximation-ratio proofs for robotic path planning algorithms, and studies how targeted context augmentation can improve proof reasoning.