7 papers
HEAD-QA v2: Expanding a Healthcare Benchmark for Reasoning
Alexis Correa-Guillén, Carlos Gómez-RodrÃguez, David Vilares
We introduce HEAD-QA v2, an expanded and updated version of a Spanish/English healthcare multiple-choice reasoning dataset originally released by Vilares and Gómez-RodrÃguez (201…
Bringing Emerging Architectures to Sequence Labeling in NLP
Ana Ezquerro, Carlos Gómez-RodrÃguez, David Vilares
Pretrained Transformer encoders are the dominant approach to sequence labeling. While some alternative architectures-such as xLSTMs, structured state-space models, diffusion models…
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…
Hierarchical Bracketing Encodings Work for Dependency Graphs
Ana Ezquerro, Carlos Gómez-RodrÃguez, David Vilares
We revisit hierarchical bracketing encodings from a practical perspective in the context of dependency graph parsing. The approach encodes graphs as sequences, enabling linear-time…
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…
Better Benchmarking LLMs for Zero-Shot Dependency Parsing
Ana Ezquerro, Carlos Gómez-RodrÃguez, 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…