WinoGrande
Introduced by Sakaguchi et al. in WinoGrande: An Adversarial Winograd Schema Challenge at Scale
WinoGrande is a large-scale dataset of 44k problems, inspired by the original WSC design, but adjusted to improve both the scale and the hardness of the dataset. The key steps of the dataset construction consist of (1) a carefully designed crowdsourcing procedure, followed by (2) systematic bias reduction using a novel AfLite algorithm that generalizes human-detectable word associations to machine-detectable embedding associations.
Source: WinoGrande: An Adversarial Winograd Schema Challenge at ScaleBenchmarks
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WinoGrande
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ST-MoE-32B 269B
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Papers
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