Papers by EuiYul Song

1 papers
Re3val: Reinforced and Reranked Generative Retrieval (2024.findings-eacl)

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Challenge: generative retrieval models encode pointers to information in a corpus as an index within the model’s parameters.
Approach: They propose a generative retrieval model that leverages contextual information to rerank retrieved page titles and utilizes REINFORCE to maximize rewards generated by constrained decoding.
Outcome: The proposed model can't be tuned for the downstream readers as decoding the page title is a non-differentiable operation.

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