Web Reference: 3 days ago · This paper combines data pruning with movement pruning for Neural Machine Translation (NMT) to enable efficient fine-pruning. We design a dataset pruning strategy by leveraging cross-entropy scores of individual training instances. Mar 13, 2026 · To address this, we propose PADP, a progressive and adaptive data pruning method for incremental learning, which dynamically evaluates sample difficulty and its difficulty changes during... Mar 27, 2026 · Traditional methods often face high computational costs, limiting their scalability and practical use. We introduce PruneFuse, a novel strategy that leverages pruned networks for data selection and later fuses them with the original network to optimize training.
YouTube Excerpt: In this episode, Ben Sorscher, a PhD student at Stanford, sheds light on the challenges posed by the ever-increasing size of
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