SafeInferCom is a framework for improving the reliability of inference-time computation in large reasoning language models (LRLMs) used for robotic task planning. It introduces a verifier-guided approach to preserve valid intermediate plans and correct errors during generation, leading to improved planning success and reduced token usage.