This workshop explores using world models to advance Physical AI and address key challenges in robot learning, reasoning, and control. Recent breakthroughs in world modeling (e.g., Genie 3, Cosmos, Cosmos 3) have spurred significant progress in enabling robots to reason (e.g., Du et al. 2024, Physical Intelligence 2026), learn (e.g., Hafner et al. 2025), and be evaluated (e.g., Gemini Robotics Team 2025) in imagined scenarios. Furthermore, integrating spatiotemporal physical dynamics into control policies (World Action Models) has led to the emergence of zero-shot and visuomotor control policies (e.g., DreamZero, Cosmos Policy). However, state-of-the-art world models are primarily vision-focused and function essentially as controllable video generation models with plausible physical dynamics. The real world is far more complex, and fundamental challenges persist in consistency, physical accuracy, and the lack of multi-modalities for physical interactions. The goal of this workshop is to bring together researchers and practitioners working at the frontiers of developing Physical AI with world models. We aim to exchange ideas on the state-of-the-art of controllable video models and discuss the critical challenges the community faces in bridging the gap between simulated dynamics and real-world physical interactions.
Location: TBD
Room Capacity: TBD
| Time | Event |
|---|---|
| 8:50 - 9:00 | Opening Remarks |
| 9:00 - 10:00 | Invited Talk 1 & 2 |
| 10:00 - 10:15 | Coffee Break |
| 10:15 - 11:00 | Oral Presentations |
| 11:00 - 12:00 | Invited Talk 3 & 4 |
| 12:00 - 13:00 | Lunch |
| 13:00 - 14:00 | Poster Session 1 |
| 14:00 - 15:30 | Invited Talk 5, 6, 7 |
| 15:30 - 16:15 | Demo & Networking |
| 16:15 - 16:30 | Coffee Break |
| 16:30 - 17:15 | Panel Discussion |
| 17:15 - 18:00 | Poster Session 2 |
All times are in Australian Eastern Standard Time (AEST).
We invite the submission of research papers, position papers, and demo proposals on the topic of world models for robot learning. This workshop focuses on the intersection of world models and robotics, exploring how predictive models of environment dynamics can advance Physical AI.
Topics of interest include, but are not limited to:
Submission Types:
Important Dates (Tentative):
Accepted papers will be presented during poster sessions, with exceptional submissions selected for spotlight oral presentations.
All accepted papers will be made publicly available as non-archival reports, allowing for future submissions to archival conferences or journals.
Please submit your papers to the Open Review site. For demo and networking proposals, please submit 1 page PDF to the google form.
Please incorporate reviewers’ feedback and prepare your camera-ready submission. Please submit your camera-ready version on OpenReview. Your camera-ready submission should be de-anonymized and include at most 8 pages for full papers, and 2-4 pages for short papers, excluding references and appendices. The paper format must follow the NeurIPS style template.
The camera-ready deadline is November 30, 2026, Anywhere on Earth (AoE).