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GAUDI: A Neural Architect for Immersive 3D Scene Generation., , , , , , , , , and 2 other author(s). NeurIPS, (2022)Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?, , , , , , , , , and . EMNLP (Findings), page 12342-12364. Association for Computational Linguistics, (2023)Gradual Domain Adaptation in the Wild: When Intermediate Distributions are Absent., , , , , and . CoRR, (2021)Expanded N-Grams for Semantic Text Alignment Notebook for PAN at CLEF 2014., , , and . CLEF (Working Notes), volume 1180 of CEUR Workshop Proceedings, page 928-938. CEUR-WS.org, (2014)Blackbox meets blackbox: Representational Similarity and Stability Analysis of Neural Language Models and Brains, , , and . (2019)cite arxiv:1906.01539.Robust Evaluation of Language-Brain Encoding Experiments., , and . CICLing (1), volume 13451 of Lecture Notes in Computer Science, page 44-61. Springer, (2019)Scale Efficiently: Insights from Pretraining and Finetuning Transformers., , , , , , , , , and . ICLR, OpenReview.net, (2022)Experiential, Distributional and Dependency-based Word Embeddings have Complementary Roles in Decoding Brain Activity., , , and . CMCL, page 57-66. Association for Computational Linguistics, (2018)Long Range Arena: A Benchmark for Efficient Transformers, , , , , , , , , and . (2020)cite arxiv:2011.04006.A Comparison of Architectures and Pretraining Methods for Contextualized Multilingual Word Embeddings., , and . AAAI, page 9090-9097. AAAI Press, (2020)