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cs.CL2024

Dancing in the syntax forest: fast, accurate and explainable sentiment analysis with SALSA

Carlos Gómez-Rodríguez, Muhammad Imran, David Vilares +2

Sentiment analysis is a key technology for companies and institutions to gauge public opinion on products, services or events. However, for large-scale sentiment analysis to be acc…

cs.CL2024

From Partial to Strictly Incremental Constituent Parsing

Ana Ezquerro, Carlos Gómez-Rodríguez, David Vilares

We study incremental constituent parsers to assess their capacity to output trees based on prefix representations alone. Guided by strictly left-to-right generative language models…

cs.CL2023

4 and 7-bit Labeling for Projective and Non-Projective Dependency Trees

Carlos Gómez-Rodríguez, Diego Roca, David Vilares

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 lab…

cs.CL2023

On the Challenges of Fully Incremental Neural Dependency Parsing

Ana Ezquerro, Carlos Gómez-Rodríguez, David Vilares

Since the popularization of BiLSTMs and Transformer-based bidirectional encoders, state-of-the-art syntactic parsers have lacked incrementality, requiring access to the whole sente…

cs.CL2023

Assessment of Pre-Trained Models Across Languages and Grammars

Alberto Muñoz-Ortiz, David Vilares, Carlos Gómez-Rodríguez

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…

cs.CL2023

Another Dead End for Morphological Tags? Perturbed Inputs and Parsing

Alberto Muñoz-Ortiz, David Vilares

The usefulness of part-of-speech tags for parsing has been heavily questioned due to the success of word-contextualized parsers. Yet, most studies are limited to coarse-grained tag…