@inproceedings{na-min-2020-jbnu,
    title = "{JBNU} at {MRP} 2020: {AMR} Parsing Using a Joint State Model for Graph-Sequence Iterative Inference",
    author = "Na, Seung-Hoon  and
      Min, Jinwoo",
    editor = "Oepen, Stephan  and
      Abend, Omri  and
      Abzianidze, Lasha  and
      Bos, Johan  and
      Haji{\v{c}}, Jan  and
      Hershcovich, Daniel  and
      Li, Bin  and
      O'Gorman, Tim  and
      Xue, Nianwen  and
      Zeman, Daniel",
    booktitle = "Proceedings of the CoNLL 2020 Shared Task: Cross-Framework Meaning Representation Parsing",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/2020.conll-shared.8/",
    doi = "10.18653/v1/2020.conll-shared.8",
    pages = "83--87",
    abstract = "This paper describes the Jeonbuk National University (JBNU) system for the 2020 shared task on Cross-Framework Meaning Representation Parsing at the Conference on Computational Natural Language Learning. Among the five frameworks, we address only the abstract meaning representation framework and propose a joint state model for the graph-sequence iterative inference of (Cai and Lam, 2020) for a simplified graph-sequence inference. In our joint state model, we update only a single joint state vector during the graph-sequence inference process instead of keeping the dual state vectors, and all other components are exactly the same as in (Cai and Lam, 2020)."
}