Autors: Gergov, I., Tsochev, G. R.
Title: Watermarking Fine-Tuning Datasets for Robust Provenance
Keywords: dataset watermarking, fine-tuning datasets, model provenance, synonym-based embedding, secret-key masking

References

    Issue

    APPLIED SCIENCES-BASEL, vol. 15, 2025, Switzerland, https://doi.org/10.3390/app151910457

    Цитирания (Citation/s):
    1. Islam, MR, Uddin, MP, Xiang, Y, Are LLM watermarks reliable in practice? A systematic review of evidence, robustness, threat models, and deployment assumptions, COMPUTER SCIENCE REVIEW, vol 63, 2027, issn: 1574-0137, eissn: 1876-7745, art_no: ARTN 101074, doi: 10.1016/j.cosrev.2026.101074 - 2026 - в издания, индексирани в Web of Science

    Вид: статия в списание, публикация в издание с импакт фактор, публикация в реферирано издание, индексирана в Scopus и Web of Science