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Meta-Learning Deep Energy-Based Memory Models., , , and . CoRR, (2019)Stabilizing Transformers for Reinforcement Learning., , , , , , , , , and 3 other author(s). CoRR, (2019)Compressive Transformers for Long-Range Sequence Modelling., , , , and . ICLR, OpenReview.net, (2020)Unified Scaling Laws for Routed Language Models., , , , , , , , , and 16 other author(s). CoRR, (2022)Scaling Language Models: Methods, Analysis & Insights from Training Gopher., , , , , , , , , and 70 other author(s). CoRR, (2021)Fast Parametric Learning with Activation Memorization., , , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 4225-4234. PMLR, (2018)Meta-Learning Neural Bloom Filters., , and . CoRR, (2019)Top-KAST: Top-K Always Sparse Training., , , , and . CoRR, (2021)Stabilizing Transformers for Reinforcement Learning., , , , , , , , , and 3 other author(s). ICML, volume 119 of Proceedings of Machine Learning Research, page 7487-7498. PMLR, (2020)Do Transformers Need Deep Long-Range Memory?, and . ACL, page 7524-7529. Association for Computational Linguistics, (2020)