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Our objective is to introduce to the NLP community an existing k-NN searchlibrary NMSLIB, a new retrieval toolkit FlexNeuART, as well as theirintegration capabilities. NMSLIB, while being one the fastest k-NN searchlibraries, is quite generic and supports a variety of distance/similarityfunctions. Because the library relies on the distance-based structure-agnosticalgorithms, it can be further extended by adding new distances. FlexNeuART is amodular, extendible and flexible toolkit for candidate generation in IR and QAapplications, which supports mixing of classic and neural ranking signals.FlexNeuART can efficiently retrieve mixed dense and sparse representations(with weights learned from training data), which is achieved by extendingNMSLIB. In that, other retrieval systems work with purely sparserepresentations (e.g., Lucene), purely dense representations (e.g., FAISS andAnnoy), or only perform mixing at the re-ranking stage.

Flexible retrieval with NMSLIB and FlexNeuART