[Meetings] [CFP] Workshop on Reinforcement Learning for Vision-Language-Action Models (RL4VLA) at RSS 2026

[Alap Kshirsagar]

Dear all,

We are excited to announce the Workshop on Reinforcement Learning for Vision-Language-Action Models (RL4VLA) at RSS 2026, taking place on July 17, 2026, in Sydney, Australia. Paper submissions are now open! Submit your work by June 8th, 2026.

As robotics foundation models continue to scale, reinforcement learning is playing an increasingly important role in improving reasoning, long-horizon decision-making, interaction, and real-world adaptation in Vision Language Action (VLA) systems. The RL4VLA Workshop brings together researchers across robotics, reinforcement learning, embodied AI, and multimodal foundation models to discuss the future of scalable and general-purpose robot learning.

Workshop Website: https://sites.google.com/view/rl4vla-workshop
Workshop Date: July 17, 2026
Location: Sydney, Australia
Submission Deadline: June 8, 2026 (AoE)
Submission Portal (OpenReview): https://openreview.net/group?id=roboticsfoundation.org/RSS/2026/Workshop/RL4VLA
Reviewer Sign-Up Form: https://forms.gle/AsHBPvKK7D37Ax7o7

Topics of Interest
• RL fine-tuning of multimodal foundation models for robotics
• Offline and batch RL for language-conditioned policies
• Reward modeling and preference-based RL for embodied agents
• Human-in-the-loop reinforcement learning for VLA
• Hierarchical and model-based RL for multimodal planning
• Sim-to-real transfer in RL-based VLA systems
• Safety and robustness in RL-trained language-conditioned agents
• Benchmarks for evaluating RL in Vision-Language-Action models

We are excited to host leading researchers from academia and industry and look forward to vibrant discussions on how reinforcement learning can enhance the reasoning, adaptability, and real-world capabilities of Vision-Language-Action (VLA) systems and embodied robotic agents.

We look forward to your submissions and participation.

Best regards,
RL4VLA Workshop Organizers 

(Ahmed Hendawy, Alap Kshirsagar, Yufeng Jin, Carlo D'Eramo, Georgia Chalvatzaki, Jan Peters, Rudolf Lioutikov)