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arXiv:1905.00537cs.CL

SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems

Alex Wang, Yada Pruksachatkun, Nikita Nangia, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, Samuel R. Bowman

Early discovery. Linked by one identifiable commenter. This paper is outside the main ranking; a mention is not an endorsement.

Abstract

In the last year, new models and methods for pretraining and transfer learning have driven striking performance improvements across a range of language understanding tasks. The GLUE benchmark, introduced a little over one year ago, offers a single-number metric that summarizes progress on a diverse set of such tasks, but performance on the benchmark has recently surpassed the level of non-expert humans, suggesting limited headroom for further research. In this paper we present SuperGLUE, a new benchmark styled after GLUE with a new set of more difficult language understanding tasks, a software toolkit, and a public leaderboard. SuperGLUE is available at super.gluebenchmark.com.

arXiv comments
NeurIPS 2019, super.gluebenchmark.com updating acknowledegments
Journal reference
DOI
Subjects
cs.CLComputation and Language cs.AIArtificial Intelligence

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    • I think classifying this as human level is misleading. Look at the sub-scores on the page. One score that looks very different from humans is AX-b. The SuperGlue paper provides more context about AX-b https://arxiv.org/pdf/1905.00537.pdf AX-b "is the broad-coverage diagnostic…

      RcouF1uZ4gsCView on HNParent context

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