ListarGI-LYS - Congresos, conferencias, etc. por tema "Sequence labeling"
Mostrando ítems 1-5 de 5
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4 and 7-bit Labeling for Projective and Non-Projective Dependency Trees
(Association for Computational Linguistics, 2023-12)[Absctract]: We introduce an encoding for parsing as sequence labeling that can represent any projective dependency tree as a sequence of 4-bit labels, one per word. The bits in each word’s label represent (1) whether it ... -
Assessment of Pre-Trained Models Across Languages and Grammars
(Association for Computational Linguistics, 2023-11)[Absctract]: We present an approach for assessing how multilingual large language models (LLMs) learn syntax in terms of multi-formalism syntactic structures. We aim to recover constituent and dependency structures by ... -
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 ... -
Sequence Labeling Parsing by Learning across Representations
(Association for Computational Linguistics, 2019-07)[Absctract]: We use parsing as sequence labeling as a common framework to learn across constituency and dependency syntactic abstractions. To do so, we cast the problem as multitask learning (MTL). First, we show that ... -
Sequence Tagging for Fast Dependency Parsing
(2019)[Abstract] Dependency parsing has been built upon the idea of using parsing methods based on shift-reduce or graph-based algorithms in order to identify binary dependency relations between the words in a sentence. In this ...
