Summary of Mitigate the Gap: Investigating Approaches For Improving Cross-modal Alignment in Clip, by Sedigheh Eslami and Gerard De Melo
Mitigate the Gap: Investigating Approaches for Improving Cross-Modal Alignment in CLIP
by Sedigheh Eslami, Gerard de Melo
First submitted to arxiv on: 25 Jun 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper presents a new approach to Contrastive Language-Image Pre-training (CLIP) that addresses the pronounced modality gap in the CLIP embedding space. This gap makes the embedding space overly sparse and disconnected, with different modalities being densely distributed in distinct subregions of the hypersphere. The authors design AlignCLIP, a method that reduces this gap by sharing the parameter space between multi-modal encoders and pushing apart uni-modal embeddings via intra-modality separation. Extensive experiments demonstrate that AlignCLIP achieves noticeable enhancements in cross-modal alignment of embeddings, reducing the modality gap while improving performance across various zero-shot and fine-tuning downstream evaluations. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper improves a language-image model called CLIP by making it work better with different types of data. Right now, the model has trouble combining information from different sources like text and images. The authors try to fix this problem by sharing resources between different parts of the model and moving them apart a bit. They test their new approach, called AlignCLIP, and show that it works much better than the original method. |
Keywords
» Artificial intelligence » Alignment » Embedding space » Fine tuning » Multi modal » Zero shot
