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README.md

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 # UniHGKR-base-beir
 
+Our paper: [UniHGKR: Unified Instruction-aware Heterogeneous Knowledge Retrievers](https://arxiv.org/abs/2410.20163).
+
 The UniHGKR-base-beir model is derived from the UniHGKR-base model, further fine-tuned on MS MARCO for evaluation on the BEIR benchmark. We recommend using the [sentence-transformers](https://www.SBERT.net) package to load our model and to perform embedding for paragraphs and sentences.
 
 It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
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 ## Citation
 
-### BibTeX
+If you find this resource useful in your research, please consider giving a like and citation.
+
+```
+@article{min2024unihgkr,
+  title={UniHGKR: Unified Instruction-aware Heterogeneous Knowledge Retrievers},
+  author={Min, Dehai and Xu, Zhiyang and Qi, Guilin and Huang, Lifu and You, Chenyu},
+  journal={arXiv preprint arXiv:2410.20163},
+  year={2024}
+}
+```
 
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 ## Glossary