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Parsing as Pretraining
(2020)
[Abstract] Recent analyses suggest that encoders pretrained for language
modeling capture certain morpho-syntactic structure.
However, probing frameworks for word vectors still do not report
results on standard setups ...
Towards Robust Word Embeddings for Noisy Texts
(MDPI, 2020)
[Abstract] Research on word embeddings has mainly focused on improving their performance on standard corpora, disregarding the difficulties posed by noisy texts in the form of tweets and other types of non-standard writing ...
On the Use of Parsing for Named Entity Recognition
(MDPI, 2021-01-25)
[Abstract] Parsing is a core natural language processing technique that can be used to obtain the structure underlying sentences in human languages. Named entity recognition (NER) is the task of identifying the entities ...
Optimality of syntactic dependency distances
(American Physical Society, 2022-01)
[Abstract]: It is often stated that human languages, as other biological systems, are shaped by cost-cutting pressures but, to what extent? Attempts to quantify the degree of optimality of languages by means of an optimality ...
Discontinuous grammar as a foreign language
(Elsevier, 2023-03)
[Abstract] In order to achieve deep natural language understanding, syntactic constituent parsing is a vital step, highly demanded by many artificial intelligence systems to process both text and speech. One of the most ...
Multitask Pointer Network for Multi-Representational Parsing
(Elsevier, 2022-01-25)
[Abstract] Dependency and constituent trees are widely used by many artificial intelligence applications for representing the syntactic structure of human languages. Typically, these structures are separately produced by ...
Dependency parsing with bottom-up Hierarchical Pointer Networks
(Elsevier, 2023-03)
[Abstract] Dependency parsing is a crucial step towards deep language understanding and, therefore, widely demanded by numerous Natural Language Processing applications. In particular, left-to-right and top-down transition-based ...
Transition-based semantic role labeling with pointer networks
(Elsevier, 2023-01-25)
[Abstract] Semantic role labeling (SRL) focuses on recognizing the predicate–argument structure of a sentence and plays a critical role in many natural language processing tasks such as machine translation and question ...