Building Scalable Infrastructure for Robot Learning:
From Data Scaling to Real-World Deployment

This workshop focuses on four interconnected pillars:

• Data Scaling: Exploring scalable strategies for acquiring, generating, and orchestrating multimodal data across real-world interactions and simulations.
• Training and Post-Training: Examining supervised fine-tuning, imitation learning, reinforcement learning, preference learning, and scalable training workflows for embodied agents.
• Evaluation: Developing standardized benchmarking protocols and methodologies to assess generalization, long-horizon reasoning, safety, robustness, and data efficiency.
• Deployment Infrastructure: Building reliable software-hardware integration pipelines and continuous feedback loops to support real-world robot execution and fleet learning.

Scope of Accepted Papers

We invite submissions that address the system-level challenges in scalable robot learning. Topics of interest include, but are not limited to:

• Real-world robot interaction data collection and large-scale teleoperation pipelines
• Simulation data generation, synthetic multimodal data, and sim-to-real transfer
• Supervised fine-tuning, imitation learning, and post-training workflows for VLA models
• Offline and online reinforcement learning, and preference learning for embodied agents
• Benchmarking VLA capabilities, long-horizon reasoning, and task generalization
• Safety, robustness assessment, and reliable evaluation methodologies for real robots
• Infrastructure for continuous deployment, hardware-software integration, and fleet learning
• Distributed experimentation and runtime diagnostics for real-world robot execution systems

Submission Details

Submissions will be managed through OpenReview and reviewed using a double-blind process. We welcome research papers, system and infrastructure reports, benchmark or evaluation papers, work in progress, and negative or failure-case studies that provide practical insight for the community.

This is a non-proceedings workshop. Accepted submissions will not be included in official proceedings, and we welcome submissions that present or extend previously published work for discussion with the workshop community.

• Submission site: OpenReview submission page.
• Format: IROS / IEEE two-column conference template.
• Length: No more than 8 pages, including references.

Accepted submissions will be presented through selected paper talks or interactive poster presentations. We plan to select three submissions for oral presentation.