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A Neural Corpus Indexer for Document Retrieval
[article]
2023
arXiv
pre-print
Current state-of-the-art document retrieval solutions mainly follow an index-retrieve paradigm, where the index is hard to be directly optimized for the final retrieval target. In this paper, we aim to show that an end-to-end deep neural network unifying training and indexing stages can significantly improve the recall performance of traditional methods. To this end, we propose Neural Corpus Indexer (NCI), a sequence-to-sequence network that generates relevant document identifiers directly for
arXiv:2206.02743v3
fatcat:ac2azatiz5g3nemelwo5btku6u