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All Projects → oaqa → Flexneuart

oaqa / Flexneuart

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Flexible classic and NeurAl Retrieval Toolkit

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neural-networksquestion-answeringinformation-retrieval

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FlexNeuART (flex-noo-art)

Flexible classic and NeurAl Retrieval Toolkit, or shortly FlexNeuART (intended pronunciation flex-noo-art) is a substantially reworked knn4qa package. The overview can be found in our EMNLP OSS workshop paper: Flexible retrieval with NMSLIB and FlexNeuART, 2020. Leonid Boytsov, Eric Nyberg.

In Aug-Dec 2020, we used this framework to generate best traditional and/or neural runs in the MSMARCO Document ranking task. In fact, our best traditional (non-neural) run slightly outperformed a couple of neural submissions. The code for the best-performing neural model will be published within 2-3 months. This model is described in our ECIR 2021 paper: Boytsov, Leonid, and Zico Kolter. "Exploring Classic and Neural Lexical Translation Models for Information Retrieval: Interpretability, Effectiveness, and Efficiency Benefits." ECIR 2021.

FlexNeuART is under active development. More detailed description and documentaion is to appear. Currently we have:

For neural network training FlexNeuART incorporates a re-worked variant of CEDR (MacAvaney et al' 2019).

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