EPISODE · Jun 13, 2026 · 8 MIN
EP244: Learning to Hand Off
from Learning GenAI via SOTA Papers - Video · host Yun Wu
Title: Learning to Hand Off: Provably Convergent Workflow Learning under Interface ConstraintsSource: http://arxiv.org/abs/2605.19140v1Summary:This research provides the first finite-sample guarantee for neural Q-learning in decentralized multi-agent settings, a foundational breakthrough for reliable agentic workflow learning. By formalizing handoffs as interface-constrained SMDPs, it enables provably convergent learning in complex LLM pipelines where agents have restricted observability.
What this episode covers
Title: Learning to Hand Off: Provably Convergent Workflow Learning under Interface ConstraintsSource: http://arxiv.org/abs/2605.19140v1Summary:This research provides the first finite-sample guarantee for neural Q-learning in decentralized multi-agent settings, a foundational breakthrough for reliable agentic workflow learning. By formalizing handoffs as interface-constrained SMDPs, it enables provably convergent learning in complex LLM pipelines where agents have restricted observability.
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EP244: Learning to Hand Off
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