# Can Question Rewriting Help Conversational Question Answering?

Source: [Can Question Rewriting Help Conversational Question Answering?](<https://www.sota2.com/research/paper/68fa6c3b1e209131cea32eb1>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T00:06:48.603Z

Authors: Etsuko Ishii, Yan Xu, Samuel Cahyawijaya, Bryan Wilie

Published: 2022-04-13T08:16:03.000Z

## Abstract

Question rewriting (QR) is a subtask of conversational question answering (CQA) aiming to ease the challenges of understanding dependencies among dialogue history by reformulating questions in a self-contained form. Despite seeming plausible, little evidence is available to justify QR as a mitigation method for CQA. To verify the effectiveness of QR in CQA, we investigate a reinforcement learning approach that integrates QR and CQA tasks and does not require corresponding QR datasets for targeted CQA. We find, however, that the RL method is on par with the end-to-end baseline. We provide an analysis of the failure and describe the difficulty of exploiting QR for CQA.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2204.06239>)

[PDF](<https://arxiv.org/pdf/2204.06239.pdf>)