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LLM agents trained with simulated user and tool noise not only become more robust in messy real-world environments, but also surprisingly improve on clean, idealized benchmarks.
VLMs can't count blocks because they lack a view-consistent spatial interface, but decomposing scenes into orthographic projections fixes it.
