The first large-scale annotated mobile full-waveform LiDAR dataset for ghost artifact detection and removal, with 24,412 frames and 7.5 billion peak-level annotations — 100× more than prior work. Ghost points arise from multi-path reflections off glass and reflective surfaces, degrading 3D mapping and object detection in autonomous driving. Includes FWL-MAE pretraining and transformer-based detection baselines across Ghost, Object, Glass, and Noise categories.