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Allocating additional computation during decision-making boosts long-horizon robot manipulation success by significantly enhancing subtask prediction accuracy.
Current LLMs falter in domain-specific reasoning, revealing critical gaps that Benchmark Agent's evolving benchmarks can help address.
