Workshop on Planning in the Era of LLMs (LM4Plan @ ICAPS 2025)
ICAPS 2025 Workshop, Melbourne, Australia, Date: 10-11 November, 2025
Visit https://llmforplanning.github.io/ for up-to-date information.
Overview
Large Language Models (LLMs) are a disruptive force, changing how research was done in many sub-areas of AI. Planning is one of the last bastions that remain standing. The focus of this workshop is on the questions in the intersection of these areas. Some of the specific areas we would like to gain a better understanding in include: what LLMs can contribute to planning, how LLMs can/should be used, what are the pitfalls of using LLMs, what are the guarantees that can be obtained.
Topics of Interest
We invite paper submissions on the following (not exhaustive) list of topics:
- Algorithms and theories of planning with pre-trained or fine-tuned LLMs.
- LLMs for (partial) model elicitation.
- LLMs for search guidance or search pruning.
- LLMs for planning modulo theories.
- LLMs as proxies for user preferences.
- Validation/verification of plans, policies, or models.
- Generalization in planning and generalized planning with LLMs.
- Using LLMs to develop interfaces for planning-related problems.
- Other applications of LLMs in planning.
- Other applications of large vision-language models (VLMs) in planning.
- Planning for LLMs and VLMs.
Important Dates
- Paper submission deadline: August 5th, 2025, AoE (extended)
- Paper acceptance notification: September 8th, 2025, AoE
ICAPS will be in-person this year. Authors of accepted workshop papers are expected to register for the workshop, physically attend the conference and present in person.
Submission Details
We solicit workshop paper submissions relevant to the above call of the following types:
- Long papers – up to 8 pages + unlimited references / appendices
- Short papers – up to 4 pages + unlimited references / appendices
Please format submissions in AAAI style (see instructions in the Author Kit of the ICAPS 2025 Call for Papers). Authors submitting papers rejected from other conferences, please ensure you do your utmost to address the comments given by the reviewers. Please do not submit papers that are already accepted for the main ICAPS conference to the workshop.
Paper submissions should be made through OpenReview.
Accepted Papers
- PDDL-Instruct: Enhancing Symbolic Planning Capabilities in LLMs through Logical Chain-of-Thought Instruction Tuning
Pulkit Verma, Ngoc La, Anthony Favier, Swaroop Mishra, Julie Shah - Language Models For Generalised PDDL Planning: Synthesising Sound and Programmatic Policies
Dillon Ze Chen, Johannes Zenn, Tristan Cinquin, Sheila A. McIlraith - Planner-Independent Extraction of Goals and Constraints from Natural Language for Open-World Mobile Robot Missions
Björn Döschl, Jane Jean Kiam - Game of Thought: Robust Information Seeking with Large Language Models Using Game Theory
Langyuan Cui, Hwee Tou Ng, Chun Kai Ling - Automated Repair of Totally-Ordered Hierarchical Task Network Domains via Context-Free Grammars with Large Language Model Support
Daniel Lutalo, Pascal Bercher - Which LLM is Best for Translating Natural Language Goals to PDDL
Tomas Balyo, Lukas Chrpa, G Michael Youngblood - Improved Generalized Planning with LLMs through Strategy Refinement and Reflection
Katharina Stein, Nils Hodel, Daniel Fišer, Jörg Hoffmann, Michael Katz, Alexander Koller - From Next Token Prediction to (STRIPS) World Models – Preliminary Results
Carlos Núñez-Molina, Vicenç Gomez, Hector Geffner - A Collaborative Numeric Task Planning Framework based on Constraint Translations using LLMs
Anthony Favier, Ngoc La, Pulkit Verma, Julie Shah - Seemingly Simple Planning Problems are Computationally Challenging: The Countdown Game
Michael Katz, Harsha Kokel, Sarath Sreedharan - Guiding Exploration in Reinforcement Learning Through LLM-Augmented Observations
Vaibhav Jain, Gerrit Großmann - Towards a General Framework for HTN Modeling with LLMs
Israel Puerta-Merino, Carlos Núñez-Molina, Pablo Mesejo, Juan Fernandez-Olivares - A Requirements Engineering-Driven Methodology for Planning Domain Generation via LLMs with Invariant-Based Refinement
Angelo Casciani, Giuseppe De Giacomo, Andrea Marrella, Christoph Weinhuber - Enhancing GPT-based Planning Policies by Model-based Plan Validation
Nicholas Rossetti, Massimiliano Tummolo, Alfonso Gerevini, Matteo Olivato, Luca Putelli, Ivan Serina
The papers will be available only after the workshop.
Organizing Committee
- Pascal Bercher, Australian National Univeristy
- Augusto B. Corrêa, University of Oxford
- Morgan Fine-Morris, Naval Research Laboratory
- Michael Katz, IBM Research
- Sarath Sreedharan, Colorado State University