GoldiCLIP: The Goldilocks Approach for Balancing Explicit Supervision for Language-Image Pretraining

ArXi:2603.24804v1 Announce Type: cross Until recently, the success of large-scale vision-language models (VLMs) has primarily relied on billion-sample datasets, posing a significant barrier to progress. Latest works have begun to close this gap by improving supervision quality, but each addresses only a subset of the weaknesses in contrastive pre