mlsanityData to 7 Oct 2026

A Roadmap to Guide the Integration of LLMs in Hierarchical Planning

arXiv 2501.08068 ↗First posted 14 Jan 2025cs.AIcited by 7

On the map: LLM reasoning → Reasoning for agents, planning and code

Abstract (arXiv)

Recent advances in Large Language Models (LLMs) are fostering their integration into several reasoning-related fields, including Automated Planning (AP). However, their integration into Hierarchical Planning (HP), a subfield of AP that leverages hierarchical knowledge to enhance planning performance, remains largely unexplored. In this preliminary work, we propose a roadmap to address this gap and harness the potential of LLMs for HP. To this end, we present a taxonomy of integration methods, exploring how LLMs can be utilized within the HP life cycle. Additionally, we provide a benchmark with a standardized dataset for evaluating the performance of future LLM-based HP approaches, and present initial results for a state-of-the-art HP planner and LLM planner. As expected, the latter exhibits limited performance (3% correct plans, and none with a correct hierarchical decomposition) but serves as a valuable baseline for future approaches.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Placed in Reasoning for agents, planning and code, one of 17 directions in LLM reasoning. Builds on 16 of its 22 references that are in the map. First posted on arXiv 14 Jan 2025.

Builds on

16 of 22 references.

Closest ancestors · 2

Same direction, newest first

  1. 2023Reasoning with Language Model is Planning with World Model24 May
  2. 2023On the Planning Abilities of Large Language Models (A Critical Investigation with a Proposed Benchmark)13 Feb

Other references · 14

  1. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,601
  2. 2022Large Language Models are Zero-Shot Reasonerscited by 4,323
  3. 2023Reflexion: Language Agents with Verbal Reinforcement Learningcited by 4,064
  4. 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,500
  5. 2023Self-Refine: Iterative Refinement with Self-Feedbackcited by 3,317
  6. 2022Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agentscited by 1,029
  7. 2023LLM+P: Empowering Large Language Models with Optimal Planning Proficiencycited by 496
  8. 2024Understanding the planning of LLM agents: A surveycited by 414
  9. 2024HelpSteer2-Preference: Complementing Ratings with Preferencescited by 129
  10. 2020Keep CALM and Explore: Language Models for Action Generation in Text-based Gamescited by 108
  11. 2023LLM-Assist: Enhancing Closed-Loop Planning with Language-Based Reasoningcited by 59
  12. 2024On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS)cited by 40
2 more
  1. 2024NL2Plan: Robust LLM-Driven Planning from Minimal Text Descriptionscited by 22
  2. 2024OceanPlan: Hierarchical Planning and Replanning for Natural Language AUV Piloting in Large-scale Unexplored Ocean Environmentscited by 7

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 5; 2026: 2.

7 papers.

  1. 2025Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Modelscited by 381
  2. 2025ReMA: Learning to Meta-think for LLMs with Multi-Agent Reinforcement Learningcited by 78
  3. 2025LLMs as Planning Formalizers: A Survey for Leveraging Large Language Models to Construct Automated Planning Modelscited by 38
  4. 2025ChatHTN: Interleaving Approximate (LLM) and Symbolic HTN Planningcited by 7
  5. 2026ProGAL-VLA: Grounded Alignment through Prospective Reasoning in Vision-Language-Action Modelscited by 1
  6. 2025Towards a General Framework for HTN Modeling with LLMscited by 0
  7. 2026QueryGraph: Reliable Multi-Tool Query Execution Planning via LLM-Based Graph Generationcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Large Language Models for Planning: A Comprehensive and Systematic Survey
  2. 2024Chasing Progress, Not Perfection: Revisiting Strategies for End-to-End LLM Plan Generation
  3. 2025Language Model as Planner and Formalizer under Constraints
  4. 2022PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change
  5. 2023On the Planning Abilities of Large Language Models : A Critical Investigation
  6. 2025Complex LLM Planning via Automated Heuristics Discovery
  7. 2026Knowledge Model Prompting Increases LLM Performance on Planning Tasks
  8. 2024LLMs Can't Plan, But Can Help Planning in LLM-Modulo Frameworks