Reevaluating the Intra-Modal Misalignment Hypothesis in CLIP
Recent research suggested that the embeddings produced by CLIP-like contrastive language-image training are suboptimal for image-only tasks. The main theory is that the inter-modal (language-image) alignment loss ignores intra-modal (image-image) alignment, leading to poorly calibrated distances between images. In this study, we question this intra-modal misalignment hypothesis. We reexamine its foundational theoretical argument, the indicators used to support it, and the performance metrics affected. For the theoretical argument, we demonstrate that there are no such supposed degrees of freedom for image embedding distances. For the empirical measures, our findings reveal they yield simi...
| Authors | Jonas Herzog, Yue Wang |
|---|---|
| Primary category | cs.CV |
| Published | 17 March 2026 |
| Last updated at source | 24 May 2026 |
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