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Larger sliding-window attention can paradoxically slow down the formation of critical retrieval mechanisms in language models, challenging conventional design assumptions.
LLMs can significantly enhance their collaborative performance, achieving over 24% better engagement with human partners when trained in realistic game scenarios.
