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| Model | Pretrain Model | Train w/ Marco Title | Marco Dev MRR@10 | BEIR Avg NDCG@10 |
|---|---|---|---|---|
| ANCE-Tele | cocodr-base | w/o | 37.3 | 44.2 |
| BERI Dataset | NDCG@10 |
|---|---|
| TREC-COVID | 77.4 |
| NFCorpus | 34.4 |
| FiQA | 29.0 |
| ArguAna | 45.6 |
| Touché-2020 | 22.3 |
| Quora | 85.8 |
| SCIDOCS | 14.6 |
| SciFact | 71.0 |
| NQ | 50.5 |
| HotpotQA | 58.8 |
| Signal-1M | 27.2 |
| TREC-NEWS | 34.7 |
| DBPedia-entity | 36.2 |
| Fever | 71.4 |
| Climate-Fever | 17.9 |
| BioASQ | 42.1 |
| Robust04 | 41.4 |
| CQADupStack | 34.9 |
@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}
}