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arXiv 2011.02686cs.CL

Investigating Societal Biases in a Poetry Composition System

USC Information Sciences Institute(南加州大学信息科学研究所);Google Research(谷歌研究院)

Emily Sheng, David Uthus

英文摘要:

There is a growing collection of work analyzing and mitigating societal biases in language understanding, generation, and retrieval tasks, though examining biases in creative tasks remains underexplored. Creative language applications are meant for direct interaction with users, so it is important to quantify and mitigate societal biases in these applications. We introduce a novel study on a pipeline to mitigate societal biases when retrieving next verse suggestions in a poetry composition system. Our results suggest that data augmentation through sentiment style transfer has potential for mitigating societal biases.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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