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  license: mit
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  license: mit
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+ This model is the **query** encoder of ANCE-Tele trained on TriviaQA, 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.
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+ 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.
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+ |NQ (Test)|R@5|R@20|R@20|
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+ |:---|:---|:---|:---|
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+ |ANCE-Tele|76.9|83.4|87.3|
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+ ```
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+ @inproceedings{sun2022ancetele,
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+ title={Reduce Catastrophic Forgetting of Dense Retrieval Training with Teleportation Negatives},
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+ author={Si Sun, Chenyan Xiong, Yue Yu, Arnold Overwijk, Zhiyuan Liu and Jie Bao},
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+ booktitle={Proceedings of EMNLP 2022},
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+ year={2022}
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+ }
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+ ```