BrickBench is a benchmark for agentic text-conditioned LEGO-set design, evaluating agents' ability to create physically buildable assemblies that meet semantic and design criteria. It includes a testing environment called BrickAgent for validating designs.
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Useful for evaluating how well AI agents can design LEGO sets that are both semantically aligned and physically buildable.
The paper introduces Trace2Env, a learning-free framework that uses historical interaction traces to create a reusable environment worldbook for simulating realistic environments without rebuilding the original system. It improves next-observation fidelity and long-horizon interaction consistency compared to conventional prompt-based language world models.
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4 days ago