The Trinity: Capability-Driven Recursive Self-Improvement for Multimodal Agents

This paper introduce The Trinity, a recursive self-improvement framework designed to scale multimodal intelligence by coupling automated environment generation with agent evolution. Instead of relying on traditional task-specific optimization, the system groups diverse tasks into a hierarchical capability tree based on shared underlying requirements. Through a process called Capability-Driven Real2Sim2Real, the framework constructs simplified, verifiable simulation worlds where specialized Harness configurations continuously refine their reusable modules. A Capability-Aware Harness Router then utilizes public task information and verified execution experience to match new tasks with the most suitable Harness branch. Ultimately, this approach successfully improves performance across numerous training and unseen benchmarks while demonstrating effective transfer to physical, real-world embodied settings.