Paper proposes residual-completion method for stateful handoffs between AI agents
A new arXiv preprint addresses the problem of transferring control between tool-using AI models without discarding work already done. The authors frame it as commitment-constrained residual completion, where a handoff must carry over accepted decisions, effects already produced, and outstanding obligations rather than restarting the task. The approach targets routing and cascade setups that cut costs by passing control between models.