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Evaluating Open-Weight E-Commerce Agents with Environment-Grounded Verification

arXiv · AI, language, vision and robotics · article · Sep 14, 2026 · UTC

A shopping conversation has many routes to the same cart, and a task-success rate reduces all of them to one score. We build a deterministic and reproducible e-commerce environment that precommits each trial's customer and trajectory parameters, including the persona, difficulty, target cart, and an item reveal schedule. A simulated consumer attempts to buy a target cart from the environment with assistance from the evaluated model. The environment guides the simulator's actions and records every assistant action alongside the environment state at that point. After the trial, these records all

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