[Mova](https://md.mova.elamur.ai/free/en/) · [this page in HTML](https://mova.elamur.ai/free/en/docs/papers/authors/kareem-darwish/) [home](https://md.mova.elamur.ai/free/en/) / [docs](https://md.mova.elamur.ai/free/en/docs/) / [papers](https://md.mova.elamur.ai/free/en/docs/papers/) / [authors](https://md.mova.elamur.ai/free/en/docs/papers/authors/) / Kareem Darwish # Kareem Darwish 7 paper cards in Mova's library · 2002–2024 Kareem Darwish wrote 7 of the papers Mova reads, in 2002–2024, most of them on [Treebanks](https://md.mova.elamur.ai/free/en/docs/papers/topics/treebanks/); often with [Ahmed Abdelali](https://md.mova.elamur.ai/free/en/docs/papers/authors/ahmed-abdelali/), [Hamdy Mubarak](https://md.mova.elamur.ai/free/en/docs/papers/authors/hamdy-mubarak/), [Mohamed Eldesouki](https://md.mova.elamur.ai/free/en/docs/papers/authors/mohamed-eldesouki/). [OpenAlex](https://openalex.org/A5111452036) · [**h-index 38**](https://openalex.org/authors/A5111452036) · [4980 citations](https://openalex.org/authors/A5111452036) · [151 works](https://openalex.org/works?filter=author.id:A5111452036) — openalex, 2026-10-18 The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Kareem+Darwish) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Kareem+Darwish) · [dblp](https://dblp.org/search?q=Kareem+Darwish) · [ACL Anthology](https://aclanthology.org/search/?q=Kareem+Darwish) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Kareem+Darwish) Topics: [Treebanks](https://md.mova.elamur.ai/free/en/docs/papers/topics/treebanks/) 1 ## Papers 1. **[Arabic Diacritization Using Morphologically Informed Character-Level Model](https://md.mova.elamur.ai/free/en/docs/papers/coling-2024-elmallah-arabic-diacritization-morphologically-informed-character/)** *(2024)* The paper restores Arabic short vowels with a character-level recurrent model, and adds the morpheme boundaries that a separate segmenter predicts. 2. **[Arabic Diacritization: Stats, Rules, and Hacks](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2017-darwish-arabic-diacritization-stats-rules-hacks/)** *(2017)* The diacritizer works in two cascaded steps. First it restores the vowels of the word core (the word without its case ending): a word-level bigram model with a Viterbi decoder, backed off to stem dictionaries, stem templates derived from roots (computed with Farasa), a transliteration-mined model for foreign names (a… 3. **[A Neural Architecture for Dialectal Arabic Segmentation](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2017-samih-neural-architecture-dialectal-arabic-segmentation/)** *(2017)* Egyptian Arabic in tweets has no standard spelling and few annotated resources, and the clitics attached to its verbs are missed by MSA tools. 4. **[Arabic Multi-Dialect Segmentation: bi-LSTM-CRF vs. SVM](https://md.mova.elamur.ai/free/en/docs/papers/langstream-2017-eldesouki-arabic-multi-dialect-segmentation-bi/)** *(2017)* The paper segments four Arabic dialects (Egyptian, Levantine, Gulf, Maghrebi) from raw Twitter text. Only about 350 manually segmented tweets per dialect are used for training, with 5-fold cross-validation and a 70/10/20 split. Two approaches are compared. An SVM ranker generates all segmentations of a word from a… 5. **[Farasa: A Fast and Furious Segmenter for Arabic](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2016-abdelali-farasa-fast-furious-segmenter-arabic/)** *(2016)* Farasa splits an Arabic word into prefixes, stem and suffixes. Every character-level split that uses a legal prefix and suffix sequence is generated, and a linear SVM-rank model scores the candidates. The features are stem and affix likelihoods, lexicon membership (a list of valid stems, a gazetteer of names, a list… 6. **[Using Stem-Templates to Improve Arabic POS and Gender/Number Tagging](https://md.mova.elamur.ai/free/en/docs/papers/lingbulk-2014-darwish-stem-templates-improve-arabic-pos/)** *(2014)* The paper builds an end-to-end Arabic pipeline: correction of common spelling confusions (alef forms, ta marbuta and ha, alef maqsura and ya), character-level segmentation with a CRF, POS tagging with a CRF, and gender and number tagging for nouns and adjectives. 7. **[Building a Shallow Arabic Morphological Analyser in One Day](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2002-darwish-building-shallow-arabic-morphological-analyser/)** *(2002)* The paper describes Sebawai, a shallow analyser that returns candidate roots for an Arabic word and is learned from word-root pairs. ## Co-authors (16) - [Ahmed Abdelali](https://md.mova.elamur.ai/free/en/docs/papers/authors/ahmed-abdelali/) ×5 - [Hamdy Mubarak](https://md.mova.elamur.ai/free/en/docs/papers/authors/hamdy-mubarak/) ×5 - [Mohamed Eldesouki](https://md.mova.elamur.ai/free/en/docs/papers/authors/mohamed-eldesouki/) ×2 - [Mohammed Attia](https://md.mova.elamur.ai/free/en/docs/papers/authors/mohammed-attia/) ×2 - [Younes Samih](https://md.mova.elamur.ai/free/en/docs/papers/authors/younes-samih/) ×2 - Abdelrahman El-Sheikh - Ashraf Hatim Elneima - Kallmeyer Laura - Laura Kallmeyer - [Mahmoud Reda](https://md.mova.elamur.ai/free/en/docs/papers/authors/mahmoud-reda/) - [Mohamed Al-Badrashiny](https://md.mova.elamur.ai/free/en/docs/papers/authors/mohamed-al-badrashiny/) - Muhammad Morsy Elmallah - Murtadha Aljubran - [Nadir Durrani](https://md.mova.elamur.ai/free/en/docs/papers/authors/nadir-durrani/) - Nouf Alsaeed - Reem Mohammed - [← previous Kais Dukes](https://md.mova.elamur.ai/free/en/docs/papers/authors/kais-dukes/) - [next → Karl Moritz Hermann](https://md.mova.elamur.ai/free/en/docs/papers/authors/karl-moritz-hermann/) - [↑ back to Authors](https://md.mova.elamur.ai/free/en/docs/papers/authors/)