论文标题

NLP研究人员认为什么? NLP社区Metasurvey的结果

What Do NLP Researchers Believe? Results of the NLP Community Metasurvey

论文作者

Michael, Julian, Holtzman, Ari, Parrish, Alicia, Mueller, Aaron, Wang, Alex, Chen, Angelica, Madaan, Divyam, Nangia, Nikita, Pang, Richard Yuanzhe, Phang, Jason, Bowman, Samuel R.

论文摘要

我们介绍了NLP社区Metasurvey的结果。从2022年5月到2022年6月,该调查引起了关于有争议的问题的意见,包括该领域的行业影响,对AGI和道德的关注。我们的结果将具体数字置于几个争议中:例如,受访者几乎完全将有关人工通用智能的重要性的问题分为一半,语言模型是否理解语言以及语言结构的必要性以及对解决NLP问题的必要性。此外,调查提出了元问题,要求受访者预测调查响应的分布。这不仅使我们不仅可以深入了解NLP研究人员所拥有的各种信念,还可以揭示社区预测与现实不符的错误社会学信念。我们在广泛的问题上发现这种不匹配。除其他结果外,社区大大高估了其对基准有用性的信念,以及扩展解决现实世界中问题的潜力,同时低估了其对语言结构,归纳偏见和跨学科科学重要性的信念。

We present the results of the NLP Community Metasurvey. Run from May to June 2022, the survey elicited opinions on controversial issues, including industry influence in the field, concerns about AGI, and ethics. Our results put concrete numbers to several controversies: For example, respondents are split almost exactly in half on questions about the importance of artificial general intelligence, whether language models understand language, and the necessity of linguistic structure and inductive bias for solving NLP problems. In addition, the survey posed meta-questions, asking respondents to predict the distribution of survey responses. This allows us not only to gain insight on the spectrum of beliefs held by NLP researchers, but also to uncover false sociological beliefs where the community's predictions don't match reality. We find such mismatches on a wide range of issues. Among other results, the community greatly overestimates its own belief in the usefulness of benchmarks and the potential for scaling to solve real-world problems, while underestimating its own belief in the importance of linguistic structure, inductive bias, and interdisciplinary science.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源