mlsanityData to 14 Oct 2026

UniMorph 2.0: Universal Morphology

arXiv 1810.11101 ↗First posted 25 Oct 2018cs.CLcited by 42

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Abstract (arXiv)

The Universal Morphology UniMorph project is a collaborative effort to improve how NLP handles complex morphology across the world's languages. The project releases annotated morphological data using a universal tagset, the UniMorph schema. Each inflected form is associated with a lemma, which typically carries its underlying lexical meaning, and a bundle of morphological features from our schema. Additional supporting data and tools are also released on a per-language basis when available. UniMorph is based at the Center for Language and Speech Processing (CLSP) at Johns Hopkins University in Baltimore, Maryland and is sponsored by the DARPA LORELEI program. This paper details advances made to the collection, annotation, and dissemination of project resources since the initial UniMorph release described at LREC 2016. lexical resources} }

Key facts. Cited by 42 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 Oct 2018.

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Citing papers per year: 2021: 15; 2022: 8; 2023: 5; 2024: 5; 2025: 4; 2026: 5.

42 papers.

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  1. 2021On the Pitfalls of Analyzing Individual Neurons in Language Modelscited by 62
  2. 2024Why do language models perform worse for morphologically complex languages?cited by 62
  3. 2025Large Language Models Share Representations of Latent Grammatical Concepts Across Typologically Diverse Languagescited by 59
  4. 2024Probing the Emergence of Cross-lingual Alignment during LLM Trainingcited by 39
  5. 2023Universal NER: A Gold-Standard Multilingual Named Entity Recognition Benchmarkcited by 26
  6. 2025MorphBPE: A Morpho-Aware Tokenizer Bridging Linguistic Complexity for Efficient LLM Training Across Morphologiescited by 25
  7. 2021(Un)solving Morphological Inflection: Lemma Overlap Artificially Inflates Models' Performancecited by 20
  8. 2022Same Neurons, Different Languages: Probing Morphosyntax in Multilingual Pre-trained Modelscited by 14
  9. 2021Can a Transformer Pass the Wug Test? Tuning Copying Bias in Neural Morphological Inflection Modelscited by 13
  10. 2021Probing as Quantifying Inductive Biascited by 12
  11. 2022UniMorph 4.0: Universal Morphologycited by 11
  12. 2021Evaluating the Morphosyntactic Well-formedness of Generated Textscited by 8
30 more
  1. 2024Evaluating Subword Tokenization: Alien Subword Composition and OOV Generalization Challengecited by 8
  2. 2021Morph Call: Probing Morphosyntactic Content of Multilingual Transformerscited by 5
  3. 2021Neural Morphology Dataset and Models for Multiple Languages, from the Large to the Endangeredcited by 5
  4. 2023A Joint Matrix Factorization Analysis of Multilingual Representationscited by 5
  5. 2021RuSentEval: Linguistic Source, Encoder Force!cited by 4
  6. 2021On the Effectiveness of Dataset Embeddings in Mono-lingual,Multi-lingual and Zero-shot Conditionscited by 4
  7. 2022Morphological Processing of Low-Resource Languages: Where We Are and What's Nextcited by 4
  8. 2023K-UniMorph: Korean Universal Morphology and its Feature Schemacited by 4
  9. 2021Rule-based Morphological Inflection Improves Neural Terminology Translationcited by 3
  10. 2021Morpheme Boundary Detection & Grammatical Feature Prediction for Gujarati : Dataset & Modelcited by 3
  11. 2022CaMEL: Case Marker Extraction without Labelscited by 3
  12. 2023On the Role of Morphological Information for Contextual Lemmatizationcited by 3
  13. 2021Searching for Search Errors in Neural Morphological Inflectioncited by 2
  14. 2021Computational Morphology with Neural Network Approachescited by 2
  15. 2021Not quite there yet: Combining analogical patterns and encoder-decoder networks for cognitively plausible inflectioncited by 2
  16. 2022Dim Wihl Gat Tun: The Case for Linguistic Expertise in NLP for Underdocumented Languagescited by 2
  17. 2023Morphological Inflection: A Reality Checkcited by 2
  18. 2024Recent advancements in computational morphology : A comprehensive surveycited by 2
  19. 2021Apurin~a Universal Dependencies Treebankcited by 1
  20. 2026When Irregularity Helps: A Subclass Analysis of Inductive Bias in Neural Morphologycited by 1
  21. 2022Cross-lingual Inflection as a Data Augmentation Method for Parsingcited by 0
  22. 2022The Open corpus of the Veps and Karelian languages: overview and applicationscited by 0
  23. 2022Word-Level Representation From Bytes For Language Modelingcited by 0
  24. 2024Dravidian language family through Universal Dependencies lenscited by 0
  25. 2025Flexing in 73 Languages: A Single Small Model for Multilingual Inflectioncited by 0
  26. 2025Corpus Frequencies in Morphological Inflection: Do They Matter?cited by 0
  27. 2026CommonMorph: Participatory Morphological Documentation Platformcited by 0
  28. 2026Zero-Shot Morphological Discovery in Low-Resource Bantu Languages via Cross-Lingual Transfer and Unsupervised Clusteringcited by 0
  29. 2026BLiMPPI: Benchmark of Linguistic Minimal Pairs for Polarity Itemscited by 0
  30. 2026From Copying to Composition: How Language Models Develop In-Context Learningcited by 0