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Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?

, , , , , , , , , и . EMNLP (Findings), стр. 12342-12364. Association for Computational Linguistics, (2023)

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Emergent Abilities of Large Language Models., , , , , , , , , и 6 other автор(ы). Trans. Mach. Learn. Res., (2022)Language GANs Falling Short., , , , , и . CoRR, (2018)Scaling Instruction-Finetuned Language Models., , , , , , , , , и 25 other автор(ы). J. Mach. Learn. Res., (2024)Deep Graph Infomax., , , , , и . ICLR (Poster), OpenReview.net, (2019)Revisiting Fundamentals of Experience Replay., , , , , , и . ICML, том 119 из Proceedings of Machine Learning Research, стр. 3061-3071. PMLR, (2020)Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models., , , , , , , , , и 440 other автор(ы). Trans. Mach. Learn. Res., (2023)Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step., , , , , и . ICLR (Poster), OpenReview.net, (2018)Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?, , , , , , , , , и . EMNLP (Findings), стр. 12342-12364. Association for Computational Linguistics, (2023)Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models., , , , , , , , , и 440 other автор(ы). CoRR, (2022)Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity., , и . J. Mach. Learn. Res., (2022)