Analysing the Robustness of Dual Encoders for Dense Retrieval Against Misspellings

This repository contains resources for the paper: Analysing the Robustness of Dual Encoders for Dense Retrieval Against Misspellings. In: Proceedings of SIGIR 2022

Challenging test sets

Challenging test sets where typos appear in random words, non-stop words, as well as highly discriminative utterances, can be found under the "test" directory.

Download trained models and results.

Download the pretrained retrieval models and the retrieval results:

bash download.sh

Citation

If you find this work helpful or use it in your own work, please cite our paper.

@inproceedings{10.1145/3477495.3531818,
author = {Sidiropoulos, Georgios and Kanoulas, Evangelos},
title = {Analysing the Robustness of Dual Encoders for Dense Retrieval Against Misspellings},
year = {2022},
isbn = {9781450387323},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3477495.3531818},
doi = {10.1145/3477495.3531818},
booktitle = {Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {2132–2136},
numpages = {5},
location = {Madrid, Spain},
series = {SIGIR '22}
}