Fabian Drexel

A ViT-B/3D encoder trained on 113,611 thoraco-abdomino-pelvic CT volumes, TAP-JEPA, matches state-of-the-art CT encoders on thoracic and abdominal classification benchmarks; replaying its exact masking, teacher and predictor shows hidden-target prediction lowers mean Skill from 0.388 to 0.271 for pathology but only from 0.921 to 0.873 for anatomy. Pathology moves 34.7% toward matched controls along the teacher direction while controls move 13.6% toward pathology, with larger shifts farther from visible context, and deleting all final-layer pathology tokens changes the decision margin by at most 0.45% in four of seven scan-level probes.

A ViT-B/3D encoder trained on 113,611 thoraco-abdomino-pelvic CT volumes, TAP-JEPA, matches state-of-the-art CT encoders on thoracic and abdominal classification benchmarks; replaying its exact masking, teacher and predictor shows hidden-target prediction lowers mean Skill from 0.388 to 0.271 for pathology but only from 0.921 to 0.873 for anatomy. Pathology moves 34.7% toward matched controls along the teacher direction while controls move 13.6% toward pathology, with larger shifts farther from visible context, and deleting all final-layer pathology tokens changes the decision margin by at most 0.45% in four of seven scan-level probes.