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D4: Improving LLM Pretraining via Document De-Duplication and Diversification., , , и . CoRR, (2023)Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language Models., , , и . NeurIPS, (2022)Investigating Generalization by Controlling Normalized Margin., , , , и . ICML, том 162 из Proceedings of Machine Learning Research, стр. 6324-6336. PMLR, (2022)Text Quality-Based Pruning for Efficient Training of Language Models., , , , , , , , , и 1 other автор(ы). CoRR, (2024)Effective pruning of web-scale datasets based on complexity of concept clusters., , , , , и . CoRR, (2024)Dynatask: A Framework for Creating Dynamic AI Benchmark Tasks., , , , , , , , , и . ACL (demo), стр. 174-181. Association for Computational Linguistics, (2022)Decoding Data Quality via Synthetic Corruptions: Embedding-guided Pruning of Code Data., , , , , , , , , и . CoRR, (2023)The Unreasonable Ineffectiveness of the Deeper Layers., , , , и . CoRR, (2024)SemDeDup: Data-efficient learning at web-scale through semantic deduplication., , , , и . CoRR, (2023)Ensemble Machine Learning Methods for Modeling COVID19 Deaths., , , и . CoRR, (2020)