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license: mit
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# LongD-CLIP
# Retaining Knowledge and Enhancing Long-Text Representations in CLIP through Dual-Teacher Distillation
📄 **CVPR 2025**
This repository provides resources for our CVPR 2025 paper:
**"Retaining Knowledge and Enhancing Long-Text Representations in CLIP through Dual-Teacher Distillation"**
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## 🔍 Introduction
Our work focuses on **improving CLIP’s ability to handle long-text inputs** while retaining its original knowledge.
We propose a **Dual-Teacher Distillation** framework that:
- Retains knowledge from the original CLIP,
- Enhances long-text representations through teacher guidance,
This work **extends the research line of [Long-CLIP](https://github.com/beichenzbc/Long-CLIP)** and further advances long-text representation learning in multimodal models.
👉 The implementation can also **refer to [LongD-CLIP](https://github.com/yourname/LongD-CLIP)**.
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## 🚀 Resources
- **Paper**: [CVPR 2025 proceedings](https://openaccess.thecvf.com/content/CVPR2025/papers/Feng_Retaining_Knowledge_and_Enhancing_Long-Text_Representations_in_CLIP_through_Dual-Teacher_CVPR_2025_paper.pdf)
- **Model Weights**: [Hugging Face – LongD-CLIP](https://huggingface.co/BruceFeng98/LongD-CLIP/tree/main)
- **Related Codebase**: [Long-CLIP](https://github.com/beichenzbc/Long-CLIP)
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