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Efficient Retrieval Optimized Multi-task Learning
[article]
2021
arXiv
pre-print
Recently, there have been significant advances in neural methods for tackling knowledge-intensive tasks such as open domain question answering (QA). These advances are fueled by combining large pre-trained language models with learnable retrieval of documents. Majority of these models use separate encoders for learning query representation, passage representation for the retriever and an additional encoder for the downstream task. Using separate encoders for each stage/task occupies a lot of
arXiv:2104.10129v1
fatcat:br6yaaumfncdrck2wxmodmihoq