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PaLM: Scaling Language Modeling with Pathways., , , , , , , , , and 57 other author(s). CoRR, (2022)FCM: Forgetful Causal Masking Makes Causal Language Models Better Zero-Shot Learners., , , , , , and . CoRR, (2022)Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer., , , , , , , , and . CoRR, (2019)Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer., , , , , , , , and . J. Mach. Learn. Res., (2020)UniMax: Fairer and More Effective Language Sampling for Large-Scale Multilingual Pretraining., , , , , , and . ICLR, OpenReview.net, (2023)Character-Aware Models Improve Visual Text Rendering., , , , , , , , , and . ACL (1), page 16270-16297. Association for Computational Linguistics, (2023)Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?, , , , , , , , , and . EMNLP (Findings), page 12342-12364. Association for Computational Linguistics, (2023)Scale Efficiently: Insights from Pre-training and Fine-tuning Transformers., , , , , , , , , and . CoRR, (2021)Scaling Instruction-Finetuned Language Models., , , , , , , , , and 21 other author(s). CoRR, (2022)Do Transformer Modifications Transfer Across Implementations and Applications?, , , , , , , , , and 6 other author(s). EMNLP (1), page 5758-5773. Association for Computational Linguistics, (2021)