@inproceedings{wang-etal-2025-hitsz,
    title = "{HITSZ}-{HLT} at {S}em{E}val-2025 Task 8: Multi-turn Interactive Code Generation for Question Answering on Tabular Data",
    author = "Wang, Jun  and
      Xiong, Feng  and
      Xu, Hongling  and
      Tu, Geng  and
      Xu, Ruifeng",
    editor = "Rosenthal, Sara  and
      Ros{\'a}, Aiala  and
      Ghosh, Debanjan  and
      Zampieri, Marcos",
    booktitle = "Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/transition-to-people-yaml/2025.semeval-1.302/",
    pages = "2318--2324",
    ISBN = "979-8-89176-273-2",
    abstract = "This paper introduces the system developed by the HITSZ-HLT team for SemEval-2025 Task 8: DataBench, Question-Answering over Tabular Data.The primary objective of Table Question Answering (TableQA) is to provide accurate answers to user queries by interpreting and understanding tabular data. To address this, we propose the Multi-turn Interactive Code GeneratiOn(MICO) framework. Specifically, MICO employs code generation as proxy task for TableQA and integrates feedback from the execution of the generated code via multi-turn dialogue process, thereby guiding the model towards self-correction.Experimental results demonstrate the effectiveness of our framework, achieving notable performance with a rank of 4/38 on the DataBench and 5/38 on the DataBench lite."
}