Papers with in-domain effectiveness

2 papers
CELI: Simple yet Effective Approach to Enhance Out-of-Domain Generalization of Cross-Encoders. (2024.naacl-short)

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Challenge: Existing cross-encoders do not capture all information into the [CLS] token . Xiong et al., 2021) find that the out-of-domain approach is less robust.
Approach: They introduce a cross-encoder with late interaction that incorporates a late interaction layer into existing models.
Outcome: The proposed method improves BEIR by 5% without compromising in-domain effectiveness or search latency.
Evaluating Token-Level and Passage-Level Dense Retrieval Models for Math Information Retrieval (2022.findings-emnlp)

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Challenge: a recent study has shown that dense retrieval methods are suboptimal for capturing contextual similarities in complex data.
Approach: They propose to combine a structure search method and efficient bi-encoder dense retrieval models to capture contextual similarities.
Outcome: The proposed model improves on token-level and passage-level dense retrieval tasks.

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