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Express achieves a groundbreaking reduction in approximation error and memory usage for causal attention, outperforming existing methods and enabling more efficient long-context language modeling.
Forget expensive human annotations or hallucination-prone LLM-generated data: rule-generated synthetic data can teach LLMs to compose knowledge and significantly boost multi-hop reasoning on real-world tasks.
