CLIRJan 6, 2021

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

arXiv:2101.01910v2800 citations
Originality Synthesis-oriented
AI Analysis

This framework addresses the problem of high resource requirements and reproducibility issues in open-domain QA for researchers.

This paper introduces SF-QA, a modular evaluation framework for open-domain question answering. It aims to make the task more accessible and reproducible for research groups with limited computing resources.

Although open-domain question answering (QA) draws great attention in recent years, it requires large amounts of resources for building the full system and 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.

Code Implementations1 repo
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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