Combating Market Manipulation: A Wasserstein GAN-GP Augmented, Focal-Loss TabNet for Cryptocurrency Pump-and-Dump Detection
On the primary 25-second chunk resolution, the proposed framework reached a precision of 100.0%, a recall of 85.7%, and an F1-score of 92.3% on a stratified held-out test split.
