BatsResearch/csp
Learning to compose soft prompts for compositional zero-shot learning.
This project helps machine learning researchers improve how well vision-language models can understand novel combinations of attributes and objects, like a 'striped blue chair' they've never seen before. It takes existing image-text datasets and a pre-trained vision-language model, then outputs a more accurate model capable of recognizing complex, unseen visual concepts. This is for researchers and practitioners working on advanced computer vision and natural language understanding tasks.
No commits in the last 6 months.
Use this if you need to boost the ability of large pre-trained vision-language models to recognize novel compositions (like 'spotted yellow') without fully retraining the entire model, saving significant computational resources.
Not ideal if you are looking for a pre-packaged solution for a specific business application rather than a research tool for model improvement.
Stars
94
Forks
6
Language
Python
License
BSD-3-Clause
Category
Last pushed
Sep 13, 2025
Commits (30d)
0
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