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BrickBench: Evaluating Agentic Brick Design

L5 · ResearcherResearcharXiv· 10/8/2026

Provides a novel evaluation framework for AI agents tackling complex physical design constraints and part selection problems.

AI Summary

Researchers introduce BrickBench, a for evaluating AI agents in designing physically buildable LEGO sets from text prompts.

Excerpt

We propose BrickBench, a benchmark for agentic text-conditioned LEGO-set design. Given a prompt, an agent is tasked with producing an assembly that not only satisfies semantic and design criteria, but that can also be physically built. To do so, it must select parts from a discrete library and reason jointly about local and global constraints. We score validity, alignment, and design across three settings that vary in scale and part availability. We provide BrickAgent, an environment for coding

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