SF-QA: Simple and Fair Evaluation Library for Open-domain Question Answering

Xiaopeng Lu, Kyusong Lee, Tiancheng Zhao


Abstract
Although open-domain question answering (QA) draws great attention in recent years, it requires large amounts of resources for building the full system and it is often difficult to reproduce previous results due to complex configurations. In this paper, we introduce SF-QA: simple and fair evaluation framework for open-domain QA. SF-QA framework modularizes the pipeline open-domain QA system, which makes the task itself easily accessible and reproducible to research groups without enough computing resources. The proposed evaluation framework is publicly available and anyone can contribute to the code and evaluations.
Anthology ID:
2021.eacl-demos.2
Volume:
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations
Month:
April
Year:
2021
Address:
Online
Editors:
Dimitra Gkatzia, Djamé Seddah
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
7–13
Language:
URL:
https://aclanthology.org/2021.eacl-demos.2
DOI:
10.18653/v1/2021.eacl-demos.2
Bibkey:
Cite (ACL):
Xiaopeng Lu, Kyusong Lee, and Tiancheng Zhao. 2021. SF-QA: Simple and Fair Evaluation Library for Open-domain Question Answering. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, pages 7–13, Online. Association for Computational Linguistics.
Cite (Informal):
SF-QA: Simple and Fair Evaluation Library for Open-domain Question Answering (Lu et al., EACL 2021)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingest-acl-2023-videos/2021.eacl-demos.2.pdf
Code
 soco-ai/SF-QA
Data
SQuAD