This repo provides the code of AR2. In the paper, we propose a new Adversarial Retriever-Ranker (AR2) framework, which constructs a unified minimax game for training the retriever and ranker models interactively.
This repo is still developing, feel free to report bugs and we will fix them ~
Starting with AR2, we developed a series of Text-Retrival methods.
- CodeRetriever: Unimodal and Bimodal Contrastive Learning, Xiaonan Li, Yeyun Gong, Yelong Shen, Xipeng Qiu, Hang Zhang, Bolun Yao, Weizhen Qi, Daxin Jiang, Weizhu Chen, Nan Duan arXiv, Code Paper
- Distill-VQ: Learning Retrieval Oriented Vector Quantization By Distilling Knowledge from Dense Embeddings, Shitao Xiao, Zheng Liu, Weihao Han, Jianjin Zhang, Defu Lian, Yeyun Gong, Qi Chen, Fan Yang, Hao Sun, Yingxia Shao, Denvy Deng, Qi Zhang, Xing Xie, SIGIR 2022, Code Paper
- Adversarial Retriever-Ranker for Dense Text Retrieval, Hang Zhang, Yeyun Gong, Yelong Shen, Jiancheng Lv, Nan Duan, Weizhu Chen, ICLR 2022, Code Paper
If you extend or use this work, please cite the paper where it was introduced:
@inproceedings{zhang2022ar2,
title={Adversarial Retriever-Ranker model for Dense Retrieval},
author={Hang Zhang, Yeyun Gong, Yelong Shen, Jiancheng Lv, Nan Duan, Weizhu Chen},
booktitle={ICLR},
year={2022}
}
@inproceedings{xiao2022distillvq,
title={Distill-VQ: Learning Retrieval Oriented Vector Quantization By Distilling Knowledge from Dense Embeddings},
author={Shitao Xiao, Zheng Liu, Weihao Han, Jianjin Zhang, Defu Lian, Yeyun Gong, Qi Chen, Fan Yang, Hao Sun, Yingxia Shao, Denvy Deng, Qi Zhang, Xing Xie},
booktitle={SIGIR},
year={2022}
}
@inproceedings{li2022coderetriever,
title={CodeRetriever: Unimodal and Bimodal Contrastive Learning},
author={Xiaonan Li, Yeyun Gong, Yelong Shen, Xipeng Qiu, Hang Zhang, Bolun Yao, Weizhen Qi, Daxin Jiang, Weizhu Chen, Nan Duan},
booktitle={arXiv},
year={2022}
}