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Non-Autoregressive Semantic Parsing for Compositional Task-Oriented Dialog., , , , , and . NAACL-HLT, page 2969-2978. Association for Computational Linguistics, (2021)Retrieval-Augmented Multimodal Language Modeling, , , , , , , , and . (2022)cite arxiv:2211.12561Comment: Published at ICML 2023. Blog post available at https://cs.stanford.edu/~myasu/blog/racm3/.Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning., , and . CoRR, (2020)Towards Language Agnostic Universal Representations., , and . ACL (1), page 4033-4041. Association for Computational Linguistics, (2019)Better Fine-Tuning by Reducing Representational Collapse., , , , , and . ICLR, OpenReview.net, (2021)Jointly Training Large Autoregressive Multimodal Models., , , , and . ICLR, OpenReview.net, (2024)CCQA: A New Web-Scale Question Answering Dataset for Model Pre-Training., , , , , , and . NAACL-HLT (Findings), page 2402-2420. Association for Computational Linguistics, (2022)VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding., , , , , , , and . EMNLP (1), page 6787-6800. Association for Computational Linguistics, (2021)Pre-training via Paraphrasing., , , , , and . NeurIPS, (2020)Scaling Laws for Generative Mixed-Modal Language Models., , , , , , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 265-279. PMLR, (2023)