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LLMs can now excel in high-frequency decision-making tasks like UAV pursuit, thanks to a novel reward normalization and consistency loss approach that aligns global and sub-semantic policies.
LLMs, despite their imperfections, can be surprisingly effective at causal discovery when combined with constraint-based methods, outperforming traditional statistical approaches.
