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cs.LG2026
Improving MoE Compute Efficiency by Composing Weight and Data Sparsity
Maciej Kilian, Oleg Mkrtchyan, Luke Zettlemoyer +2
Mixture-of-Experts layers achieve compute efficiency through weight sparsity: each token activates only a subset of experts. Data sparsity, where each expert processes only a subse…
cs.LG2024★ 7 cited
DataComp-LM: In search of the next generation of training sets for language models
Jeffrey Li, Alex Fang, Georgios Smyrnis +56
We introduce DataComp for Language Models (DCLM), a testbed for controlled dataset experiments with the goal of improving language models. As part of DCLM, we provide a standardize…