PinCLIP: Large-scale Foundational Multimodal Representation at Pinterest
While multi-modal Visual Language Models (VLMs) have demonstrated significant success across various domains, the integration of VLMs into recommendation and retrieval systems remains a challenge, due to issues like training objective discrepancies and serving efficiency bottlenecks. This paper introduces PinCLIP, a large-scale visual representation learning approach developed to enhance retrieval and ranking models at Pinterest by leveraging VLMs to learn image-text alignment. We propose a novel hybrid Vision Transformer architecture that utilizes a VLM backbone and a hybrid fusion mechanism to capture multi-modality content representation at varying granularities. Beyond standard image-...
| Authors | Josh Beal, Eric Kim, Jinfeng Rao et al. |
|---|---|
| Primary category | cs.CV |
| Published | 3 March 2026 |
| Last updated at source | 3 March 2026 |
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