text: • Models trained with feature prediction are supe- 
  rior to pixel prediction approaches under a frozen 
  evaluation protocol (attentive probing) and are com- 
  petitive with pixel prediction under full fine-tuning, 
  while using significantly shorter training schedules 
  (Tables 5 and 6). 
  
  • Models trained with feature prediction are more 
  label-efficient than pixel prediction approaches. De- 
  creasing the available number of labeled examples re- 
  sults in an increase in the performance gap between 
  V-JEPA and pixel-reconstruction models (Table 7). 