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Evaluating the Robustness of Retrieval Pipelines with Query Variation Generators
[article]
2022
arXiv
pre-print
Heavily pre-trained transformers for language modelling, such as BERT, have shown to be remarkably effective for Information Retrieval (IR) tasks, typically applied to re-rank the results of a first-stage retrieval model. IR benchmarks evaluate the effectiveness of retrieval pipelines based on the premise that a single query is used to instantiate the underlying information need. However, previous research has shown that (I) queries generated by users for a fixed information need are extremely
arXiv:2111.13057v3
fatcat:mgjubdswa5hdbhhiexbxcf6foq