# GenPlanX. Generation of Plans and Execution

arXiv: https://arxiv.org/abs/2506.10897 · HTML: https://mlsanity.com/paper/2506.10897/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Jun 2025.

## Built on by (most cited first, 2 of 2)

- [Bridging LLM Planning Agents and Formal Methods: A Case Study in Plan Verification](https://mlsanity.com/paper/2510.03469/) (2025)
- [Toward PDDL Planning Copilot](https://mlsanity.com/paper/2509.12987/) (2025)

## Abstract (arXiv)

Classical AI Planning techniques generate sequences of actions for complex tasks. However, they lack the ability to understand planning tasks when provided using natural language. The advent of Large Language Models (LLMs) has introduced novel capabilities in human-computer interaction. In the context of planning tasks, LLMs have shown to be particularly good in interpreting human intents among other uses. This paper introduces GenPlanX that integrates LLMs for natural language-based description of planning tasks, with a classical AI planning engine, alongside an execution and monitoring framework. We demonstrate the efficacy of GenPlanX in assisting users with office-related tasks, highlighting its potential to streamline workflows and enhance productivity through seamless human-AI collaboration.