Papers with computational processing

6 papers
Negation typology and general representation models for cross-lingual zero-shot negation scope resolution in Russian, French, and Spanish. (2021.naacl-srw)

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Challenge: Negation resolution remains an acute and continuously researched question in Natural Language Processing.
Approach: They propose to use multilingual pre-trained general representation models to detect negation scope in languages without annotated data.
Outcome: The proposed model achieves token-level F1 score between English, Spanish, French, and Russian.
Diacritics Restoration Using Neural Networks (L18-1)

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Challenge: a novel combination of character-level recurrent neural network and language model is proposed . people often replace characters with diacritics with their ASCII counterparts .
Approach: They propose a character-level recurrent neural network-based model and a language model for diacritics restoration.
Outcome: The proposed model reduces error of current best systems by 20% to 64% on four languages . it is also able to restore diacritical marks on a number of languages using the same model .
Recognition of Implicit Geographic Movement in Text (2020.lrec-1)

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Challenge: a growing field of research is analyzing the geographic movement of humans, animals, and other entities.
Approach: They created a corpus of sentences labeled as describing geographic movement or not . they used hand labeling, crowd voting and machine learning to predict more labels .
Outcome: a new method uses hand labeling, crowd voting and machine learning to predict more labels.
Quevedo: Annotation and Processing of Graphical Languages (2022.lrec-1)

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Challenge: graphical languages use images to convey meaning, but they require specialized computational processing . graphical systems use visual features and exploit the two dimensions of the page as a fundamental feature for codifying meaning .
Approach: They present a software tool for automatic processing of graphical languages . they use a command line application and library to collect and manage image datasets .
Outcome: a new software tool is developed for the processing of graphical languages . the tool provides features for the collection and management of image datasets .
Universal Grammatical Dependencies for Portuguese with CINTIL Data, LX Processing and CLARIN support (2022.lrec-1)

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Challenge: a new collection of quality language resources is presented for the computational processing of the Portuguese language . the framework for the mapping between linguistic form and meaning is centered on the notion of grammatical relation .
Approach: They propose a new set of quality language resources for the computational processing of the Portuguese language under the Universal Dependencies framework.
Outcome: The proposed framework provides for the mapping between linguistic form and meaning representations.
A Multitask Learning Approach for Diacritic Restoration (2020.acl-main)

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Challenge: Diacritics are used to specify pronunciations and meanings in many languages like Arabic.
Approach: They propose to use multi-task learning to optimize diacritic restoration with related NLP problems . they use Arabic as a case study since it has sufficient data resources for tasks .
Outcome: The proposed model outperforms baseline models and is comparable to the state-of-the-art models.

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