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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 – 10 of 10 1 Morphological Processing of Low-Resource Languages: Where We Are and What's Next ... Wiemerslage, Adam; Silfverberg, Miikka; Yang, Changbing. - : arXiv, 2022 BASE Show details 2 Dim Wihl Gat Tun: The Case for Linguistic Expertise in NLP for Underdocumented Languages ... Forbes, Clarissa; Samir, Farhan; Oliver, Bruce Harold. - : arXiv, 2022 BASE Show details 3 An FST morphological analyzer for the Gitksan language ... 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; Forbes, Clarissa; Nicolai, Garrett. - : Underline Science Inc., 2021 BASE Show details 4 Do RNN States Encode Abstract Phonological Alternations? ... NAACL 2021 2021; Hulden, Mans; Nicolai, Garrett; Silfverberg, Miikka; Tyers, Francis. - : Underline Science Inc., 2021 Abstract: Read the paper on the folowing link: https://www.aclweb.org/anthology/2021.naacl-main.435/ Abstract: Sequence-to-sequence models have delivered impressive results in word formation tasks such as morphological inflection, often learning to model subtle morphophonological details with limited training data. Despite the performance, the opacity of neural models makes it difficult to determine whether complex generalizations are learned, or whether a kind of separate rote memorization of each morphophonological process takes place. To investigate whether complex alternations are simply memorized or whether there is some level of generalization across related sound changes in a sequence-to-sequence model, we perform several experiments on Finnish consonant gradation---a complex set of sound changes triggered in some words by certain suffixes. We find that our models often---though not always---encode 17 different consonant gradation processes in a handful of dimensions in the RNN. We also show that by scaling the ... URL: https://dx.doi.org/10.48448/1rrf-8195 https://underline.io/lecture/19744-do-rnn-states-encode-abstract-phonological-alternationsquestion BASE Hide details 5 Do RNN States Encode Abstract Phonological Processes? ... Silfverberg, Miikka; Tyers, Francis; Nicolai, Garrett. - : arXiv, 2021 BASE Show details 6 SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection ... Vylomova, Ekaterina; White, Jennifer; Salesky, Elizabeth. - : arXiv, 2020 BASE Show details 7 Noise Isn't Always Negative: Countering Exposure Bias in Sequence-to-Sequence Inflection Models ... The 28th International Conference on Computational Linguistics 2020; Nicolai, Garrett; Silfverberg, Miikka. - : Underline Science Inc., 2020 BASE Show details 8 UniMorph 3.0: Universal Morphology Kirov, Christo; Nicolai, Garrett; Arkhangelskij, Timofey... In: Proceedings of the 12th Language Resources and Evaluation Conference (2020) BASE Show details 9 UniMorph 3.0: Universal Morphology ... McCarthy, Arya D.; Kirov, Christo; Grella, Matteo. - : ETH Zurich, 2020 BASE Show details 10 The SIGMORPHON 2019 Shared Task: Morphological Analysis in Context and Cross-Lingual Transfer for Inflection ... McCarthy, Arya D.; Vylomova, Ekaterina; Wu, Shijie. - : arXiv, 2019 BASE Show details

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