Pay for the Fault, Not the Flow: Label-Free In-Flow Multi-Agent Workflow Optimization
InFlowOp tries to optimize multi-agent workflows by charging only for the decisions most likely to fail.
The paper proposes a label-free cost that weighs an agent’s fit for a subtask against its runtime cost. That same cost is used before execution to choose task granularity and agent assignment, then during execution to pick the cheapest correction when a fault appears. The authors also introduce Braid, a benchmark meant to test tasks that require coordination beyond a single agent. They report gains over single-agent baselines of up to 11.97%, including 9.64% from in-flow optimization. HF Daily Papers' note
The paper proposes a label-free cost that weighs an agent’s fit for a subtask against its runtime cost. That same cost is used before execution to choose task granularity and agent assignment, then during execution to pick the cheapest correction when a fault appears. The authors also introduce Braid, a benchmark meant to test tasks that require coordination beyond a single agent. They report gains over single-agent baselines of up to 11.97%, including 9.64% from in-flow optimization. HF Daily Papers' note
score 4