OneEncoder is a lightweight framework for cross-modal alignment, focusing on efficiently integrating text and images (with future extensions to other modalities). Unlike traditional methods relying on massive modality-specific encoders, OneEncoder progressively aligns different data types, making it cost-effective and performant even on small paired datasets.
🚀 Key Features
✅ Multimodal Alignment: Initially supports text & image, with extension to other modalities.
✅ Lightweight & Efficient: Avoids full retraining when adding new modalities.
✅ Superior Performance: Outperforms models that require large specialized datasets.
