Update README.md

README.md

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 license: mit
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+This model is the passage encoder of ANCE-Tele trained on NQ, described in the EMNLP 2022 paper ["Reduce Catastrophic Forgetting of Dense Retrieval Training with Teleportation Negatives"](https://arxiv.org/pdf/2210.17167.pdf). The associated GitHub repository is available at https://github.com/OpenMatch/ANCE-Tele.
+
+ANCE-Tele only trains with self-mined negatives (teleportation negatives) without using additional negatives (e.g., BM25, other DR systems) and eliminates the dependency on filtering strategies and distillation modules.
+
+
+|NQ (Test)|R@5|R@20|R@20|
+|:---|:---|:---|:---|
+|ANCE-Tele|77.0|84.9|89.7|
+
+
+```
+@inproceedings{sun2022ancetele,
+  title={Reduce Catastrophic Forgetting of Dense Retrieval Training with Teleportation Negatives},
+  author={Si Sun, Chenyan Xiong, Yue Yu, Arnold Overwijk, Zhiyuan Liu and Jie Bao},
+  booktitle={Proceedings of EMNLP 2022},
+  year={2022}
+}
+```