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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 13 of 13 1 Estimating the Entropy of Linguistic Distributions ... Arora, Aryaman; Meister, Clara; Cotterell, Ryan. - : arXiv, 2022 BASE Show details 2 On Homophony and Rényi Entropy ... Pimentel, Tiago; Meister, Clara; Teufel, Simone. - : arXiv, 2021 BASE Show details 3 On Homophony and Rényi Entropy ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Cotterell, Ryan; Meister, Clara. - : Underline Science Inc., 2021 BASE Show details 4 Revisiting the Uniform Information Density Hypothesis ... Meister, Clara; Pimentel, Tiago; Haller, Patrick. - : arXiv, 2021 BASE Show details 5 Revisiting the Uniform Information Density Hypothesis ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Cotterell, Ryan; Haller, Patrick. - : Underline Science Inc., 2021 BASE Show details 6 Conditional Poisson Stochastic Beams ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Amini, Afra; Cotterell, Ryan. - : Underline Science Inc., 2021 BASE Show details 7 Language Model Evaluation Beyond Perplexity ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Cotterell, Ryan; Meister, Clara. - : Underline Science Inc., 2021 Abstract: Read paper: https://www.aclanthology.org/2021.acl-long.414 Abstract: We propose an alternate approach to quantifying how well language models learn natural language: we ask how well they match the statistical tendencies of natural language. To answer this question, we analyze whether text generated from language models exhibits the statistical tendencies present in the human-generated text on which they were trained. We provide a framework--paired with significance tests--for evaluating the fit of language models to these trends. We find that neural language models appear to learn only a subset of the tendencies considered, but align much more closely with empirical trends than proposed theoretical distributions (when present). Further, the fit to different distributions is highly-dependent on both model architecture and generation strategy. As concrete examples, text generated under the nucleus sampling scheme adheres more closely to the type--token relationship of natural language than text produced using ... Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics URL: https://underline.io/lecture/25838-language-model-evaluation-beyond-perplexity https://dx.doi.org/10.48448/jr48-6p89 BASE Hide details 8 A surprisal--duration trade-off across and within the world's languages ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Blasi, Damián; Cotterell, Ryan. - : Underline Science Inc., 2021 BASE Show details 9 Determinantal Beam Search ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Cotterell, Ryan; Forster, Martina. - : Underline Science Inc., 2021 BASE Show details 10 Is Sparse Attention more Interpretable? ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Augenstein, Isabelle; Cotterell, Ryan. - : Underline Science Inc., 2021 BASE Show details 11 A Cognitive Regularizer for Language Modeling ... Wei, Jason; Meister, Clara; Cotterell, Ryan. - : arXiv, 2021 BASE Show details 12 A Cognitive Regularizer for Language Modeling ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Cotterell, Ryan; Meister, Clara. - : Underline Science Inc., 2021 BASE Show details 13 If beam search is the answer, what was the question? Meister, Clara; Cotterell, Ryan; Vieira, Tim In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020) BASE Show details

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