Uncovering Hidden Intentions: Exploring Prompt Recovery for Deeper Insights into Generated Texts
<|reference_start|>Uncovering Hidden Intentions: Exploring Prompt Recovery for Deeper Insights into Generated Texts: Today, the detection of AI-generated content is receiving more and more attention. Our idea is to go beyond detection and try to recover the prompt used to generate a text. This paper, to the best of our knowledge, introduces the first investigation in this particular domain without a closed set of tasks. Our goal is to study if this approach is promising. We experiment with zero-shot and few-shot in-context learning but also with LoRA fine-tuning. After that, we evaluate the benefits of using a semi-synthetic dataset. For this first study, we limit ourselves to text generated by a single model. The results show that it is possible to recover the original prompt with a reasonable degree of accuracy.<|reference_end|>
@article{give2024uncovering,
    title={Uncovering Hidden Intentions: Exploring Prompt Recovery for Deeper
  Insights into Generated Texts},
    author={Louis Give, Timo Zaoral, Maria Antonietta Bruno},
    journal={arXiv preprint arXiv:2406.15871},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.15871},
    primaryClass={cs.CL cs.AI}
}