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pro vyhledávání: '"Khalifa, Salam"'
Modern Standard Arabic (MSA) nominals present many morphological and lexical modeling challenges that have not been consistently addressed previously. This paper attempts to define the space of such challenges, and leverage a recently proposed morpho
Externí odkaz:
http://arxiv.org/abs/2402.00385
Modern work on the cross-linguistic computational modeling of morphological inflection has typically employed language-independent data splitting algorithms. In this paper, we supplement that approach with language-specific probes designed to test as
Externí odkaz:
http://arxiv.org/abs/2310.13686
Morphological inflection is a popular task in sub-word NLP with both practical and cognitive applications. For years now, state-of-the-art systems have reported high, but also highly variable, performance across data sets and languages. We investigat
Externí odkaz:
http://arxiv.org/abs/2305.15637
Autor:
Batsuren, Khuyagbaatar, Goldman, Omer, Khalifa, Salam, Habash, Nizar, Kieraś, Witold, Bella, Gábor, Leonard, Brian, Nicolai, Garrett, Gorman, Kyle, Ate, Yustinus Ghanggo, Ryskina, Maria, Mielke, Sabrina J., Budianskaya, Elena, El-Khaissi, Charbel, Pimentel, Tiago, Gasser, Michael, Lane, William, Raj, Mohit, Coler, Matt, Samame, Jaime Rafael Montoya, Camaiteri, Delio Siticonatzi, Sagot, Benoît, Rojas, Esaú Zumaeta, Francis, Didier López, Oncevay, Arturo, Bautista, Juan López, Villegas, Gema Celeste Silva, Hennigen, Lucas Torroba, Ek, Adam, Guriel, David, Dirix, Peter, Bernardy, Jean-Philippe, Scherbakov, Andrey, Bayyr-ool, Aziyana, Anastasopoulos, Antonios, Zariquiey, Roberto, Sheifer, Karina, Ganieva, Sofya, Cruz, Hilaria, Karahóǧa, Ritván, Markantonatou, Stella, Pavlidis, George, Plugaryov, Matvey, Klyachko, Elena, Salehi, Ali, Angulo, Candy, Baxi, Jatayu, Krizhanovsky, Andrew, Krizhanovskaya, Natalia, Salesky, Elizabeth, Vania, Clara, Ivanova, Sardana, White, Jennifer, Maudslay, Rowan Hall, Valvoda, Josef, Zmigrod, Ran, Czarnowska, Paula, Nikkarinen, Irene, Salchak, Aelita, Bhatt, Brijesh, Straughn, Christopher, Liu, Zoey, Washington, Jonathan North, Pinter, Yuval, Ataman, Duygu, Wolinski, Marcin, Suhardijanto, Totok, Yablonskaya, Anna, Stoehr, Niklas, Dolatian, Hossep, Nuriah, Zahroh, Ratan, Shyam, Tyers, Francis M., Ponti, Edoardo M., Aiton, Grant, Arora, Aryaman, Hatcher, Richard J., Kumar, Ritesh, Young, Jeremiah, Rodionova, Daria, Yemelina, Anastasia, Andrushko, Taras, Marchenko, Igor, Mashkovtseva, Polina, Serova, Alexandra, Prud'hommeaux, Emily, Nepomniashchaya, Maria, Giunchiglia, Fausto, Chodroff, Eleanor, Hulden, Mans, Silfverberg, Miikka, McCarthy, Arya D., Yarowsky, David, Cotterell, Ryan, Tsarfaty, Reut, Vylomova, Ekaterina
The Universal Morphology (UniMorph) project is a collaborative effort providing broad-coverage instantiated normalized morphological inflection tables for hundreds of diverse world languages. The project comprises two major thrusts: a language-indepe
Externí odkaz:
http://arxiv.org/abs/2205.03608
We present state-of-the-art results on morphosyntactic tagging across different varieties of Arabic using fine-tuned pre-trained transformer language models. Our models consistently outperform existing systems in Modern Standard Arabic and all the Ar
Externí odkaz:
http://arxiv.org/abs/2110.06852
Autor:
Obeid, Ossama, Khalifa, Salam, Habash, Nizar, Bouamor, Houda, Zaghouani, Wajdi, Oflazer, Kemal
In this paper, we introduce MADARi, a joint morphological annotation and spelling correction system for texts in Standard and Dialectal Arabic. The MADARi framework provides intuitive interfaces for annotating text and managing the annotation process
Externí odkaz:
http://arxiv.org/abs/1808.08392
Most Arabic natural language processing tools and resources are developed to serve Modern Standard Arabic (MSA), which is the official written language in the Arab World. Some Dialectal Arabic varieties, notably Egyptian Arabic, have received some at
Externí odkaz:
http://arxiv.org/abs/1609.02960
Publikováno v:
Proceedings of the Annual Meeting of the Cognitive Science Society, vol 45, iss 45
Computational models of morphology acquisition have played a central role in debates over the nature of morphological representations. The apparent success of recent artificial neural network architectures for morphological inflection in natural lang
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______325::d209fa027d96b4590999b4d2b1390388
https://escholarship.org/uc/item/4cf1s2dr
https://escholarship.org/uc/item/4cf1s2dr
Autor:
Kodner, Jordan, Khalifa, Salam, Batsuren, Khuyagbaatar, Dolatian, Hossep, Cotterell, Ryan, Akkuş, Faruk, Anastasopoulos, Antonios, Andrushko, Taras, Arora, Aryaman, Atanalov, Nona, Bella, Gábor, Budianskaya, Elena, Ghanggo Ate, Yustinus, Goldman, Omer, Guriel, David, Guriel, Simon, Guriel-Agiashvili, Silvia, Kieraś, Witold, Krizhanovsky, Andrew, Krizhanovsky, Natalia, Marchenko, Igor, Markowska, Magdalena, Mashkovtseva, Polina, Nepommiashchaya, Maria, Rodionova, Daria, Sheifer, Karina, Serova, Alexandra, Yemelina, Anastasia, Young, Jeremiah, Vylomova, Ekaterina
Publikováno v:
Proceedings of the 19th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology
The 2022 SIGMORPHON–UniMorph shared task on large scale morphological inflection generation included a wide range of typologically diverse languages: 33 languages from 11 top-level language families: Arabic (Modern Standard), Assamese, Braj, Chukch
Publikováno v:
Diyala Agricultural Sciences Journal; 2020, Vol. 12 Issue 1, p194-205, 12p