@inproceedings{lu-etal-2025-overview,
    title = "Overview of {CCL}25-Eval Task6: {C}hinese Essay Rhetoric Recognition Evaluation ({CERRE})",
    author = "Lu, Yujiang  and
      Liu, Nuowei  and
      Ren, Yupei  and
      Zhu, Yicheng  and
      Lan, Man  and
      Bai, Xiaopeng  and
      Xu, Mofan  and
      Liao, Qingyu",
    editor = "Lin, Hongfei  and
      Li, Bin  and
      Tan, Hongye",
    booktitle = "Proceedings of the 24th {C}hina National Conference on Computational Linguistics ({CCL} 2025)",
    month = aug,
    year = "2025",
    address = "Jinan, China",
    publisher = "Chinese Information Processing Society of China",
    url = "https://preview.aclanthology.org/fix-8040/2025.ccl-2.30/",
    pages = "252--260",
    abstract = "``Literary grace in Chinese composition writing is a hallmark of linguistic sophistication, often realized through various rhetorical devices. The automatic identification and analysis of rhetorical devices in essays play a crucial role in educational NLP applications, particularly for assessing writing proficiency and facilitating pedagogical interventions. Although prior research has predominantly focused on coarse-grained recognition of limited rhetorical devices at sentence level, these approaches prove inadequate for handling complex rhetorical structures and emerging educational demands. In this paper, we present the CCL25-Eval Task6: Chinese EssayRhetoric Recognition Evaluation (CERRE), a novel framework comprising three distinct evaluation tracks at the document level: (1) Fine-grained Form-level Categories Recognition, (2)Fine-grained Content-level Categories Recognition, and (3) Rhetorical Component Extraction.The evaluation has attracted 29 registered participating teams, with 8 teams submitting valid system outputs. In particular, two participating systems demonstrated superior performance by exceeding the baseline metrics in complete evaluation criteria.''"
}