Papers with open-domain QA retrieval settings

1 papers
Joint Inference of Retrieval and Generation for Passage Re-ranking (2024.findings-eacl)

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Challenge: Existing methods for re-ranking documents are sparse and do not require training.
Approach: They propose a method that optimizes mutual information between query and passage distributions by integrating cross-encoders and generative models in the re-ranking process.
Outcome: The proposed method outperforms conventional re-rankers and language model scorers in open-domain QA retrieval settings and diverse retrieval benchmarks under zero-shot settings.

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