@inproceedings{wu-etal-2026-datashield,
    title = "{D}ata{S}hield: Uncovering Risky Fine-Tuning Data Across {LLM}s Through Consensus Subspace Alignment",
    author = "Wu, Zefeng  and
      Qi, Weiwei  and
      Chen, Jielong  and
      Zheng, Tianhang  and
      Hong, Di  and
      Lu, Chaochao  and
      He, Liang  and
      Qin, Zhan  and
      Ren, Kui",
    editor = "Lee, Hung-Yi  and
      Dev, Sunipa  and
      Li, Jessy  and
      Elliott, Desmond",
    booktitle = "Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing",
    month = oct,
    year = "2026",
    address = "Budapest, Hungary",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.emnlp-main.1941/",
    pages = "44165--44190",
    ISBN = "979-8-89176-459-0"
}