2 papers
cs.LG2025
Pretraining Frequency Predicts Compositional Generalization of CLIP on Real-World Tasks
Thaddäus Wiedemer, Yash Sharma, Ameya Prabhu +2
We investigate the success conditions for compositional generalization of CLIP models on real-world data through performance prediction. Prior work shows that CLIP requires exponen…
cs.CV2024
No "Zero-Shot" Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model Performance
Vishaal Udandarao, Ameya Prabhu, Adhiraj Ghosh +5
Web-crawled pretraining datasets underlie the impressive "zero-shot" evaluation performance of multimodal models, such as CLIP for classification/retrieval and Stable-Diffusion for…