| Challenge: | Existing methods to improve passage retrieval performance by using context-supervised pre-training are weakly correlated. |
| Approach: | They propose to use query-as-context pre-training to train passage-query pairs . they evaluate the pre-trained models on large-scale passage retrieval benchmarks . |
| Outcome: | The proposed technique improves performance on large-scale passage retrieval benchmarks and out-of-domain zero-shot benchmarks. |
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