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NeMo: a toolkit for building AI applications using Neural Modules, , , , , , , , , and 4 other author(s). (2019)cite arxiv:1909.09577Comment: 6 pages plus references.Leveraging Synthetic Targets for Machine Translation., , and . ACL (Findings), page 9365-9379. Association for Computational Linguistics, (2023)Stochastic Gradient Methods with Layer-wise Adaptive Moments for Training of Deep Networks., , , , , , , , and . CoRR, (2019)HelpSteer2: Open-source dataset for training top-performing reward models., , , , , , , , and . CoRR, (2024)Integrative Network Alignment Reveals Large Regions of Global Network Similarity in Yeast and Human, and . Bioinformatics, 27 (10): 1390--1396 (Mar 16, 2011)Topological network alignment uncovers biological function and phylogeny, , , , and . Journal of The Royal Society Interface, 7 (50): 1341--1354 (Mar 17, 2010)Geometric Evolutionary Dynamics of Protein Interaction Networks., , , and . Pacific Symposium on Biocomputing, page 178-189. World Scientific Publishing, (2010)SPGISpeech: 5, 000 Hours of Transcribed Financial Audio for Fully Formatted End-to-End Speech Recognition., , , , , , , , , and 3 other author(s). Interspeech, page 1434-1438. ISCA, (2021)Training Deep AutoEncoders for Collaborative Filtering., and . CoRR, (2017)NVIDIA NeMo's Neural Machine Translation Systems for English-German and English-Russian News and Biomedical Tasks at WMT21., , , and . WMT@EMNLP, page 197-204. Association for Computational Linguistics, (2021)