ReLEP is a novel framework that enables robots to break down abstract instructions into actionable steps while reducing hallucinations and logical errors in real-time.

• Combines implicit logical inference with hallucination mitigation techniques
• Eliminates the need for task-specific examples, making implementation practical
• Achieves effective long-horizon planning for embodied AI systems
• Advances real-time planning capabilities for robotics applications

This research represents a significant engineering breakthrough by addressing fundamental challenges in robotic planning and decision-making. The framework bridges the gap between abstract instructions and practical robot execution, potentially accelerating deployment of autonomous systems across industries.

Long-horizon Embodied Planning with Implicit Logical Inference and Hallucination Mitigation