Morphological Analysis

Latest papers

20 papers1 paper in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

Does Morphological Correctness Matter for Tokenization? A Scrambled Control Study in Tagalog
Oct 14, 2026Abdul Rehman Antall, Baidya Nath SahaSubword Tokenization Morphological Analysis
National University of Computer and Emerging Sciences (FAST-NUCES), Lahore, Pakistan · Concordia University of Edmonton, Alberta, Canada
Not All Irregularity Is Equal: Causally Isolating a Rare Failure Mode in Japanese Morphological Inflection
Sep 18, 2026Wen ZhangMorphological Analysis
An LLM-Associated Register Shift in Korean Journal Abstracts: A Morphology-Aware Excess-Vocabulary Study, 2018-2026
Sep 7, 2026Aron LeeAI-Generated Text Detection Scientific Communication
INTFRAME Research
Probing Character-level Transformers for the Spanish L-shaped Morphome
Aug 4, 2026Akhilesh Kakolu Ramarao, Kevin Tang, Wiebke Petersen +1Transformer Interpretability Transformer
Department of English Language and Linguistics, Heinrich Heine University Düsseldorf · Department of Linguistics, College of Liberal Arts and Sciences, University of Florida · Institute of Linguistics and Information Science, Heinrich Heine University Düsseldorf +1
The Morphological Core of Dungan: A Two-Dialect Finite-State Model and a Multi-Genre Evaluation
Jul 30, 2026Anton M. Alekseev, Sergey I. NikolenkoMorphological Analysis
St. Petersburg Department of the Steklov Mathematical Institute, RAS · St. Petersburg State University · Kyrgyz State Technical University named after I. Razzakov
Ossetic-COT: Designing a morphologically annotated corpus and morphological analyzer for Ossetic
Jul 6, 2026Anna Shatskikh, Alexey SorokinMorphosyntactic Tagging Morphological Analysis
Lomonosov Moscow State University · Yandex
MorfFlex: Handling Rich Morphology
Jun 23, 2026Jaroslava Hlaváčová, Marie Mikulová, Barbora Štěpánková +2Morphological Analysis
Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics, Malostranské náměstí 25, 118 00 Prague 1, Czech Republic
Morpheus: A Morphology-Aware Neural Tokenizer and Word Embedder for Turkish
Jun 17, 2026Tolga ŞakarWord Embeddings Subword Tokenization
Independent Researcher
PACUTE: Phonology-, Affix-, and Character-level Understanding of Tokens for Filipino
Jun 13, 2026Jann Railey Montalan, David Demitri Africa, Jimson Paulo Layacan +3LLM Evaluation Language Modeling
AI Singapore · Nanyang Technological University · UK AI Security Institute +2
Comonadic Morphophonology: A Compositional Framework for Context-Dependent Morphological Rules in Finnish
May 27, 2026Yongseok JangMorphological Analysis Category Theory
Independent Researcher
Formalization of Malagasy conjugation
May 26, 2026Joro Ny Aina Ranaivoarison, Eric Laporte, Baholisoa Simone RalalaoherivonyMorphological Analysis Low-Resource Language Processing
University of Antananarivo, Centre Interdisciplinaire de Recherche Appliquée au Malgache, Madagascar · Université Paris-Est, Laboratoire d'informatique Gaspard-Monge CNRS UMR 8049, F77454 Marne-la-Vallée, France
Pattern-and-root inflectional morphology: the Arabic broken plural
May 21, 2026Alexis Amid Neme, Eric LaporteMorphological Analysis
LIGM, Université Paris-Est · DLL, Universidade Federal do Espírito Santo
When Irregularity Helps: A Subclass Analysis of Inductive Bias in Neural Morphology
May 19, 2026Wen ZhangNeural Network Generalization Long-Tail Learning
Turning Intent into Specifications: A Benchmark and an Interactive User-Assistant Agent
May 13, 2026Hao Wang, Ligong Han, Kai Xu +1Requirements Engineering Software Engineering Agents
Red Hat AI Innovation · MIT-IBM Watson AI Lab · IBM Core AI
TajikNLP: An Open-Source Toolkit for Comprehensive Text Processing of Tajik (Cyrillic Script)
May 6, 2026Mullosharif K. Arabov, Karomatullo Habibullozoda, Nurali ShirinovMorphosyntactic Tagging Tokenization
Institute of Computational Mathematics and Information Technologies Kazan Federal University Kazan, Russia · Bokhtar State University named after Nosiri Khusrav Bokhtar, Tajikistan
Zero-Shot Morphological Discovery in Low-Resource Bantu Languages via Cross-Lingual Transfer and Unsupervised Clustering
Apr 24, 2026Hillary Mutisya, John MuganeLow-Resource Language Processing Morphological Analysis
Thiomi NLP · Harvard University
GLeMM: A large-scale multilingual dataset for morphological research
Apr 14, 2026Hathout Nabil, Basilio Calderone, Fiammetta Namer +1Morphological Analysis
CLLE, Comue de Toulouse · CLLE, CNRS, Université Toulouse Jean Jaurès, Toulouse, France · CLLE, UBM +4
Towards a theory of morphology-driven marking in the lexicon: The case of the state
Apr 3, 2026Mohamed El IdrissiMorphological Analysis Linguistic Typology
INALCO
Valency Classification of Mapudungun Verbal Roots. Established by the language's own morphotactics
Apr 1, 2026Andrés ChandíaMorphological Analysis
Department of Catalan Philology and General Linguistics University of Barcelona
TurkicNLP: An NLP Toolkit for Turkic Languages
Feb 22, 2026Sherzod HakimovMorphological Analysis Low-Resource Language Processing
Computational Linguistics, University of Potsdam

Oct 14, 2026J/K move · Enter open · S save

Does Morphological Correctness Matter for Tokenization? A Scrambled Control Study in Tagalog

Abdul Rehman Antall, Baidya Nath Saha

National University of Computer and Emerging Sciences (FAST-NUCES), Lahore, Pakistan · Concordia University of Edmonton, Alberta, Canada

Subword Tokenization Morphological Analysis Machine Translation

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Typology-aware tokenizers are motivated by the claim that segmentation which respects morpheme boundaries preserves information that frequency-driven segmentation destroys. Studies routinely establish that it helps while assuming the boundaries must be linguistically correct. We separate them. Tagalog marks voice with infixes (s-um-ulat 'wrote', s-in-ulat 'was written'), so the root is not contiguous and no sequence of BPE merges can recover it. We build MorphAustro-Tok, a tokenizer that emits the root as a contiguous unit followed by a positional infix token, and compare it against a corpus-matched BPE baseline and, at two of three fertility levels, against a scrambled-morpheme control that preserves morph count, invertibility and per-type consistency while randomising the pseudo-infix. Across 33 runs, MorphAustro-Tok improves Tagalog machine translation over matched BPE by 0.84, 1.49 and 3.40 mean sentence-level chrF++ points. Token count does not explain the gain, since it grows as segmentation coarsens, and neither does capacity: at the coarsest level the scrambled arm carries more parameters and scores lower. Scrambling the analysis moves the gain by less than between-seed dispersion at both controlled levels, so we detect no contribution from morphological correctness at this scale.