@inproceedings{li-etal-2024-lm,
    title = "{LM}-Interview: An Easy-to-use Smart Interviewer System via Knowledge-guided Language Model Exploitation",
    author = "Li, Hanming  and
      Yu, Jifan  and
      Li, Ruimiao  and
      Hao, Zhanxin  and
      Xuan, Yan  and
      Yuan, Jiaxi  and
      Xu, Bin  and
      Li, Juanzi  and
      Liu, Zhiyuan",
    editor = "Hernandez Farias, Delia Irazu  and
      Hope, Tom  and
      Li, Manling",
    booktitle = "Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
    month = nov,
    year = "2024",
    address = "Miami, Florida, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2024.emnlp-demo.52/",
    doi = "10.18653/v1/2024.emnlp-demo.52",
    pages = "520--528",
    abstract = "Semi-structured interviews are a crucial method of data acquisition in qualitative research. Typically controlled by the interviewer, the process progresses through a question-and-answer format, aimed at eliciting information from the interviewee. However, interviews are highly time-consuming and demand considerable experience of the interviewers, which greatly limits the efficiency and feasibility of data collection. Therefore, we introduce LM-Interview, a novel system designed to automate the process of preparing, conducting and analyzing semi-structured interviews. Experimental results demonstrate that LM-interview achieves performance comparable to that of skilled human interviewers."
}