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RideWay: Benchmarking Efficient Task Completion for Tool-Using Language Agents
AI agents are usually evaluated by whether they complete a task. In interactive service settings, a successful agent can still frustrate users by asking repeated questions, performing redundant searches, or making avoidable revisions. We introduce RideWay, an efficiency-centered benchmark for ridehailing agents in a stateful tool-calling environment, together with Efficiency Utility, a success-gated metric that discounts successful trajectories for excess tool calls and user-facing turns relative to task-specific reference effort. Human paired preferences calibrate the relative penalties, refl
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-16T01:15:21.000Z
First collected: 2026-09-20T08:20:57.646Z. This is not the publication date.