Papers with UnIte
UnIte: Uncertainty-based Iterative Document Sampling for Domain Adaptation in Information Retrieval (2026.findings-acl)
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| Challenge: | Existing methods focus on diversity but fail to capture model uncertainty. |
| Approach: | They propose a method to generalize neural retrievers to an unseen domain by generating pseudo queries on target domain documents. |
| Outcome: | The proposed method improves performance on large datasets with small and large models while limiting the learning utility of the current model. |