  Media bias can lead to increased political polarization, and thus, the need
for automatic mitigation methods is growing. Existing mitigation work displays
articles from multiple news outlets to provide diverse news coverage, but
without neutralizing the bias inherent in each of the displayed articles.
Therefore, we propose a new task, a single neutralized article generation out
of multiple biased articles, to facilitate more efficient access to balanced
and unbiased information. In this paper, we compile a new dataset NeuWS, define
an automatic evaluation metric, and provide baselines and multiple analyses to
serve as a solid starting point for the proposed task. Lastly, we obtain a
human evaluation to demonstrate the alignment between our metric and human
judgment.
