AlignPrune uses a Dynamic Alignment Score from loss trajectories to identify noisy samples more accurately than per-sample loss, improving pruning accuracy by up to 6.3% on noisy benchmarks.
Partial forward blocking: A novel data prun- ing paradigm for lossless training acceleration
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Beyond Loss Values: Robust Dynamic Pruning via Loss Trajectory Alignment
AlignPrune uses a Dynamic Alignment Score from loss trajectories to identify noisy samples more accurately than per-sample loss, improving pruning accuracy by up to 6.3% on noisy benchmarks.