FlexRAG

FlexRAG is a lightweight model designed to reduce RAG running costs while improving its generation quality. It compresses the retrieved contexts into compact embeddings and these embeddings are optimized to enhance downstream RAG performance. A key feature of FlexRAG is its flexibility, which enables effective support for diverse compression ratios and selective preservation of important contexts.

For the usage of this model, please refer to [Github Repo]

Citation Information

@inproceedings{wu2025lighter,
  title={Lighter and better: Towards flexible context adaptation for retrieval augmented generation},
  author={Wu, Chenyuan and Shao, Ninglu and Liu, Zheng and Xiao, Shitao and Li, Chaozhuo and Zhang, Chen and Wang, Senzhang and Lian, Defu},
  booktitle={Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining},
  pages={271--280},
  year={2025}
}