| Challenge: | linguistic typology is concerned with mapping out the relationships between languages with structural and functional properties. |
| Approach: | They propose a computational model which identifies known and new linguistic universals and uncovers them worthy of further linguistic investigation. |
| Outcome: | The proposed model outperforms baselines and knowledge base baselines. |
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| Challenge: | a new method is proposed to acquire typological evidence from "gold" treebanks for different languages. |
| Approach: | They propose a method for acquiring typological evidence from "gold" treebanks for different languages. |
| Outcome: | The proposed method can shed light on key issues of the linguistic typological literature. |
A Probabilistic Generative Model of Linguistic Typology (N19-1)
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| Challenge: | a generative model of languages based on principles-and-parameters posits that languages toggle on or off . linguistic typologists use a set of universal parameters to determine which languages toggle . we show that the correlation between parameters is significant, and that it is not enough to write down the set of parameters available to languages. |
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| Challenge: | linguistic typology is the classification of languages according to their linguistic properties. |
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Typological Features for Multilingual Delexicalised Dependency Parsing (N19-1)
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| Challenge: | Existing universal models to describe the syntax of languages are debated for decades . a new study examines the plausibility of universal grammars in dependency parsing . |
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A Deep Generative Model of Vowel Formant Typology (N18-1)
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| Challenge: | a recent study has investigated the nature of vowel inventories, i.e., which vowels a language contains . a probabilistic approach does not rule out linguistic systems completely, but it can position phenomena on a scale from very common to very improbable. |
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The Past, Present, and Future of Typological Databases in NLP (2023.findings-emnlp)
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| Challenge: | Typological information is inconsistent with each other and other sources of typological information, such as linguistic grammars. |
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Pragmatics in the Era of Large Language Models: A Survey on Datasets, Evaluation, Opportunities and Challenges (2025.acl-long)
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Bolei Ma, Yuting Li, Wei Zhou, Ziwei Gong, Yang Janet Liu, Katja Jasinskaja, Annemarie Friedrich, Julia Hirschberg, Frauke Kreuter, Barbara Plank
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On the Relation between Linguistic Typology and (Limitations of) Multilingual Language Modeling (D18-1)
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| Challenge: | a key challenge in cross-lingual NLP is developing general language-independent architectures that are equally applicable to any language. |
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Typology Guided Multilingual Position Representations: Case on Dependency Parsing (2023.findings-acl)
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| Challenge: | Recent multilingual models benefit from strong unified semantic representation models, but conflicting linguistic regularities may break the effectiveness of word position features in multilingual learning. |
| Approach: | They propose to combine prior knowledge from typology features and existing position vectors to create a position generation network which combines prior knowledge of a language's position space and typological characterization. |
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What Does Parameter-free Probing Really Uncover? (2024.acl-short)
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| Challenge: | Probing large language models (LLMs) has been criticized for using pre-defined label-laden target labels. |
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