@inproceedings{ezquerro-etal-2025-hierarchical-bracketing,
    title = "Hierarchical Bracketing Encodings Work for Dependency Graphs",
    author = "Ezquerro, Ana  and
      G{\'o}mez-Rodr{\'i}guez, Carlos  and
      Vilares, David",
    editor = "Christodoulopoulos, Christos  and
      Chakraborty, Tanmoy  and
      Rose, Carolyn  and
      Peng, Violet",
    booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/author-page-yu-wang-polytechnic/2025.emnlp-main.447/",
    doi = "10.18653/v1/2025.emnlp-main.447",
    pages = "8849--8862",
    ISBN = "979-8-89176-332-6",
    abstract = "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 parsing with $n$ tagging actions, and still representing reentrancies, cycles, and empty nodes. Compared to existing graph linearizations, this representation substantially reduces the label space while preserving structural information. We evaluate it on a multilingual and multi-formalism benchmark, showing competitive results and consistent improvements over other methods in exact match accuracy."
}