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Transforming gradients into a near-isotropic space can cut LLM pretraining time by 7.6% while enhancing downstream task performance.
Hot-swapping failed nodes during LLM training can be achieved with zero overhead, drastically reducing recovery time to under 40 seconds.
SCAPE achieves up to 43.3% faster LLM pre-training with 90% and 99% sparsity, all while maintaining model quality.
