@inproceedings{shen-etal-2022-easy,
    title = "Easy-First Bottom-Up Discourse Parsing via Sequence Labelling",
    author = "Shen, Andrew  and
      Koto, Fajri  and
      Lau, Jey Han  and
      Baldwin, Timothy",
    editor = "Braud, Chloe  and
      Hardmeier, Christian  and
      Li, Junyi Jessy  and
      Loaiciga, Sharid  and
      Strube, Michael  and
      Zeldes, Amir",
    booktitle = "Proceedings of the 3rd Workshop on Computational Approaches to Discourse",
    month = oct,
    year = "2022",
    address = "Gyeongju, Republic of Korea and Online",
    publisher = "International Conference on Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2022.codi-1.5/",
    pages = "35--41",
    abstract = "We propose a novel unconstrained bottom-up approach for rhetorical discourse parsing based on sequence labelling of adjacent pairs of discourse units (DUs), based on the framework of Koto et al. (2021). We describe the unique training requirements of an unconstrained parser, and explore two different training procedures: (1) fixed left-to-right; and (2) random order in tree construction. Additionally, we introduce a novel dynamic oracle for unconstrained bottom-up parsing. Our proposed parser achieves competitive results for bottom-up rhetorical discourse parsing."
}