Papers with multimodal matching
Text encoders bottleneck compositionality in contrastive vision-language models (2023.emnlp-main)
Copied to clipboard
| Challenge: | Existing multimodal models are often unable to reason about simple spatial relations or attribute attachments. |
| Approach: | They first curate CompPrompts, a set of increasingly compositional image captions that VL models should be able to capture . then train text-only recovery probes that aim to reconstruct captions from single-vector text representations produced by several VL model. |
| Outcome: | The proposed model can reconstruct captions from single-vector text representations produced by several models on a broader range of scenes compared to previous models. |