| | --- |
| | license: mit |
| | --- |
| | |
| | This model is the **passage** 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| |
| | |:---|:---|:---|:---| |
| | |ANCE-Tele|76.9|83.4|87.3| |
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|
| | ``` |
| | @inproceedings{sun2022ancetele, |
| | title={Reduce Catastrophic Forgetting of Dense Retrieval Training with Teleportation Negatives}, |
| | author={Si, Sun and Chenyan, Xiong and Yue, Yu and Arnold, Overwijk and Zhiyuan, Liu and Jie, Bao}, |
| | booktitle={Proceedings of EMNLP 2022}, |
| | year={2022} |
| | } |
| | ``` |
