Longformer for MS MARCO Document Re-ranking Task

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Authors Mohammad Aliannejadi, Amir Soleimani, Fabio Crestani, Ivan Sekulić
Journal/Conference Name arXiv preprint
Paper Category
Paper Abstract Two step document ranking, where the initial retrieval is done by a classical information retrieval method, followed by neural re-ranking model, is the new standard. The best performance is achieved by using transformer-based models as re-rankers, e.g., BERT. We employ Longformer, a BERT-like model for long documents, on the MS MARCO document re-ranking task. The complete code used for training the model can be found on https//github.com/isekulic/longformer-marco
Date of publication 2020
Code Programming Language Python

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