The study assesses ChatGPT's performance in biometric tasks like face recognition, gender detection, and age estimation. By designing prompts to elicit responses from ChatGPT regarding sensitive information, the study unveils the model's capabilities and potential vulnerabilities. Despite notable accuracy in various tasks, caution is advised when relying solely on ChatGPT for recognition purposes.
The research delves into the application of large language models (LLMs) like ChatGPT for biometric tasks. It highlights the model's ability to recognize facial identities accurately and differentiate between faces with considerable precision. The study showcases promising results in gender detection and reasonable accuracy in age estimation tasks using crafted prompts to evaluate ChatGPT's capabilities.
Furthermore, the paper discusses the importance of prompt engineering to extract sensitive information from ChatGPT despite its safeguards. The findings suggest significant potentials for LLMs and foundation models in biometrics applications while emphasizing the need for further research on their robustness.
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ข้อมูลเชิงลึกที่สำคัญจาก
by Ahmad Hassan... ที่ arxiv.org 03-06-2024
https://arxiv.org/pdf/2403.02965.pdfสอบถามเพิ่มเติม