Researchers have developed a novel system that trains AI agents to solve CAPTCHAs more effectively by learning from their own interactions. This system combines a fine-tuned YOLOv8 detector with an open-weight vision-language model (VLM) and a confidence-based router. It achieves high accuracy across various CAPTCHA classes by using the VLM's responses as training data for the detector, allowing it to adapt to new or perturbed CAPTCHA types without human annotation. This adaptive approach demonstrates that AI solvers can recover from adversarial attacks and improve with continued use, challenging the assumption that bots remain consistently failing. AI
IMPACT Demonstrates AI's ability to adapt and improve over time, potentially impacting online security measures and bot detection.
RANK_REASON Novel research demonstrating an adaptive AI system for solving CAPTCHAs. [lever_c_demoted from research: ic=1 ai=1.0]
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