6 papers
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…
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…
LyS at SemEval 2025 Task 8: Zero-Shot Code Generation for Tabular QA
Adrián Gude, Roi Santos-RÃos, Francisco Prado-Valiño +2
This paper describes our participation in SemEval 2025 Task 8, focused on Tabular Question Answering. We developed a zero-shot pipeline that leverages an Large Language Model to ge…
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…
Dependency Graph Parsing as Sequence Labeling
Ana Ezquerro, David Vilares, Carlos Gómez-RodrÃguez
Various linearizations have been proposed to cast syntactic dependency parsing as sequence labeling. However, these approaches do not support more complex graph-based representatio…