collaborators

6 papers

cs.CL2026

A Syntax-Injected Approach for Faster and More Accurate Sentiment Analysis

Muhammad Imran, Olga Kellert, Carlos Gómez-Rodríguez

Sentiment Analysis (SA) is a crucial aspect of Natural Language Processing (NLP), focusing on identifying and interpreting subjective assessments in textual content. Syntactic pars…

cs.CL2025

Nested Named Entity Recognition as Single-Pass Sequence Labeling

Alberto Muñoz-Ortiz, David Vilares, Caio Corro +1

We cast nested named entity recognition (NNER) as a sequence labeling task by leveraging prior work that linearizes constituency structures, effectively reducing the complexity of…

cs.CL2025

Hierarchical Bracketing Encodings for Dependency Parsing as Tagging

Ana Ezquerro, David Vilares, Anssi Yli-Jyrä +1

We present a family of encodings for sequence labeling dependency parsing, based on the concept of hierarchical bracketing. We prove that the existing 4-bit projective encoding bel…

cs.CL2025

Parsing the Switch: LLM-Based UD Annotation for Complex Code-Switched and Low-Resource Languages

Olga Kellert, Nemika Tyagi, Muhammad Imran +2

Code-switching presents a complex challenge for syntactic analysis, especially in low-resource language settings where annotated data is scarce. While recent work has explored the…

cs.CL2025

Comparing LLM-generated and human-authored news text using formal syntactic theory

Olga Zamaraeva, Dan Flickinger, Francis Bond +1

This study provides the first comprehensive comparison of New York Times-style text generated by six large language models against real, human-authored NYT writing. The comparison…

cs.CL2025

Better Benchmarking LLMs for Zero-Shot Dependency Parsing

Ana Ezquerro, Carlos Gómez-Rodríguez, David Vilares

While LLMs excel in zero-shot tasks, their performance in linguistic challenges like syntactic parsing has been less scrutinized. This paper studies state-of-the-art open-weight LL…