The official implementation of the paper "Learning-to-Rank Meets Language: Boosting Language-Driven Ordering Alignment for Ordinal Classification" is available.
- Release the datalist used during training.
- Release the training code and inference code of Morph dataset.
- Release pre-trained models.
This codebase is from CLIP-ReID, CLIP and OrdinalEntropy.
Check out these amazing works leveraging CLIP for number/rank problems!
If you use this code for your research, please cite our paper L2RCLIP: Boosting Language-Driven Ordering Alignment for Ordinal Classification:
@article{wang2023learning,
title={Learning-to-Rank Meets Language: Boosting Language-Driven Ordering Alignment for Ordinal Classification},
author={Wang, Rui and Li, Peipei and Huang, Huaibo and Cao, Chunshui and He, Ran and He, Zhaofeng},
journal={arXiv preprint arXiv:2306.13856},
year={2023}
}