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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 Page: 1 2 3 4 5 6 Hits 1 – 20 of 110 1 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 2 Backtranslation in Neural Morphological Inflection ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Hulden, Mans; Liu, Ling. - : Underline Science Inc., 2021 BASE Show details 3 Rule-based Morphological Inflection Improves Neural Terminology Translation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Carpuat, Marine; Xu, Weijia. - : Underline Science Inc., 2021 BASE Show details 4 Translating Headers of Tabular Data: A Pilot Study of Schema Translation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Gao, Yan; Guo, Jiaqi. - : Underline Science Inc., 2021 BASE Show details 5 An Information-Theoretic Characterization of Morphological Fusion ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Futrell, Richard; Hahn, Michael; Rathi, Neil. - : Underline Science Inc., 2021 Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.793/ Abstract: Linguistic typology generally divides synthetic languages into groups based on their morphological fusion. However, this measure has long been thought to be best considered a matter of degree. We present an information-theoretic measure, called informational fusion, to quantify the degree of fusion of a given set of morphological features in a surface form, which naturally provides such a graded scale. Informational fusion is able to encapsulate not only concatenative, but also nonconcatenative morphological systems (e.g. Arabic), abstracting away from any notions of morpheme segmentation. We then show, on a sample of twenty-one languages, that our measure recapitulates the usual linguistic classifications for concatenative systems, and provides new measures for nonconcatenative ones. We also evaluate the long-standing hypotheses that more frequent forms are more fusional, and that paradigm size anticorrelates with degree of ... Keyword: Data Management System; Machine Learning; Machine translation; Natural Language Processing URL: https://dx.doi.org/10.48448/hkt1-mw66 https://underline.io/lecture/37418-an-information-theoretic-characterization-of-morphological-fusion BASE Hide details 6 Analyzing the Surprising Variability in Word Embedding Stability Across Languages ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Burdick, Laura; Kummerfeld, Jonathan. - : Underline Science Inc., 2021 BASE Show details 7 Neural Machine Translation with Heterogeneous Topic Knowledge Embeddings ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Peng, Wei. - : Underline Science Inc., 2021 BASE Show details 8 STaCK: Sentence Ordering with Temporal Commonsense Knowledge ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Ghosal, Deepanway; Majumder, Navonil. - : Underline Science Inc., 2021 BASE Show details 9 Wikily Supervised Neural Translation Tailored to Cross-Lingual Tasks ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Callison-Burch, Chris; Rasooli, Mohammad Sadegh. - : Underline Science Inc., 2021 BASE Show details 10 Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Gheini, Mozhdeh; May, Jonathan. - : Underline Science Inc., 2021 BASE Show details 11 Rethinking Data Augmentation for Low-Resource Neural Machine Translation: A Multi-Task Learning Approach ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Esplà-Gomis, Miquel; Pérez-Ortiz, Juan Antonio. - : Underline Science Inc., 2021 BASE Show details 12 Sequence Length is a Domain: Length-based Overfitting in Transformer Models ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Bojar, Ondřej; Variš, Dušan. - : Underline Science Inc., 2021 BASE Show details 13 Speechformer: Reducing Information Loss in Direct Speech Translation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Gaido, Marco; Negri, Matteo. - : Underline Science Inc., 2021 BASE Show details 14 Data and Parameter Scaling Laws for Neural Machine Translation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Duh, Kevin; Gordon, Mitchell. - : Underline Science Inc., 2021 BASE Show details 15 A Simple Geometric Method for Cross-Lingual Linguistic Transformations with Pre-trained Autoencoders ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; De Raedt, Maarten. - : Underline Science Inc., 2021 BASE Show details 16 Universal Simultaneous Machine Translation with Mixture-of-Experts Wait-k Policy ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Feng, Yang; Zhang, Shaolei. - : Underline Science Inc., 2021 BASE Show details 17 Learning to Rewrite for Non-Autoregressive Neural Machine Translation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Feng, Xiaocheng; Geng, Xinwei. - : Underline Science Inc., 2021 BASE Show details 18 Towards Making the Most of Dialogue Characteristics for Neural Chat Translation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Fandong; Chen, Yufeng. - : Underline Science Inc., 2021 BASE Show details 19 Improving the Quality Trade-Off for Neural Machine Translation Multi-Domain Adaptation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Byrne, Bill; Domhan, Tobias. - : Underline Science Inc., 2021 BASE Show details 20 Sometimes We Want Ungrammatical Translations ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Parthasarathi, Prasanna. - : Underline Science Inc., 2021 BASE Show details Page: 1 2 3 4 5 6

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