RIZZ: Routing Interactions to Near Zero-Interference Zones for Continual Adaptation of Black-Box Agents

RIZZ (Routing Interactions to Near Zero-Interference Zones) is a new continual adaptation framework designed for black-box agents, enabling them to adapt to diverse user inputs and tasks without access to model weights. It utilizes a verifier-gated memory system and context-aware routing to dynamically manage input streams and compile prompts from various memory branches, thereby controlling interference from nonstationary feedback. This approach shows improved performance against existing state-of-the-art methods on competitive benchmarks, making it significant for practitioners developing adaptive AI systems that require robust online learning capabilities.