Summary of Exploring the Spectrum Of Visio-linguistic Compositionality and Recognition, by Youngtaek Oh et al.
Exploring the Spectrum of Visio-Linguistic Compositionality and Recognition
by Youngtaek Oh, Pyunghwan Ahn, Jinhyung Kim, Gwangmo Song, Soonyoung Lee, In So Kweon, Junmo Kim
First submitted to arxiv on: 13 Jun 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); 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 This paper investigates the connection between compositionality and recognition in Vision and Language Models (VLMs) like CLIP. VLMs excel at zero-shot image recognition, but struggle with linguistic comprehension and fine-grained text-image alignment. The authors conduct a comprehensive evaluation of existing VLMs, analyzing pre-training approaches for recognition and fine-tuning methods for compositionality. The study employs 12 benchmarks for compositionality, 21 zero-shot classification benchmarks, and two retrieval benchmarks for recognition. From 274 CLIP model checkpoints, patterns emerge between compositional understanding and recognition accuracy. The findings highlight the need to develop models that balance both capabilities and create meticulous benchmarks for compositionality. This research aims to improve VLMs by optimizing their performance in both areas. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study looks at how well computer vision and language models work together. These models are great at recognizing images, but struggle with understanding words and matching text to images. The researchers tested many existing models and found that they don’t do a good job of balancing their strengths. They want to create better models that can recognize images and understand words well. |
Keywords
» Artificial intelligence » Alignment » Classification » Fine tuning » Zero shot
