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What Changes Can Large-scale Language Models Bring? Intensive Study on HyperCLOVA: Billions-scale Korean Generative Pretrained Transformers.

, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and . EMNLP (1), page 3405-3424. Association for Computational Linguistics, (2021)

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Semantic Sentence Matching with Densely-Connected Recurrent and Co-Attentive Information., , and . AAAI, page 6586-6593. AAAI Press, (2019)Self-supervised pre-training and contrastive representation learning for multiple-choice video QA., , , , and . CoRR, (2020)What Changes Can Large-scale Language Models Bring? Intensive Study on HyperCLOVA: Billions-scale Korean Generative Pretrained Transformers., , , , , , , , , and 27 other author(s). EMNLP (1), page 3405-3424. Association for Computational Linguistics, (2021)Korean Language Modeling via Syntactic Guide., , , , and . LREC, page 2841-2849. European Language Resources Association, (2022)Unifying Vision-Language Representation Space with Single-Tower Transformer., , , , and . AAAI, page 980-988. AAAI Press, (2023)Self-Distilled Self-supervised Representation Learning., , , , , and . WACV, page 2828-2838. IEEE, (2023)Textbook Question Answering with Multi-modal Context Graph Understanding and Self-supervised Open-set Comprehension., , and . ACL (1), page 3568-3584. Association for Computational Linguistics, (2019)Semantic Sentence Matching with Densely-connected Recurrent and Co-attentive Information., , , and . CoRR, (2018)Textbook Question Answering with Knowledge Graph Understanding and Unsupervised Open-set Text Comprehension., , and . CoRR, (2018)Self-Distilled Self-Supervised Representation Learning., , , , and . CoRR, (2021)