MLDT represents an innovative approach by decomposing complex tasks for robots. It enhances LLMs planning abilities with a goal-sensitive corpus and instruction tuning on generated data, successfully tackling complex long-horizon tasks.

• Innovative decomposition strategy
• Enhanced planning abilities for LLMs
• Significant performance improvements

An advancement in robotic planning (Research Image), this method holds the potential to significantly improve autonomy and execution of complicated tasks in robotics.