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eddc3427c5d77843c2253f1e799fe933-Paper.pdf

Neural Information Processing Systems

Whileprevious work tackles this issue by using explicit labeling on the spuriously correlated attributes or presuming a particular bias type, we instead utilize a cheaper, yet generic form of human knowledge, which can be widely applicable to various types ofbias.



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Neural Information Processing Systems

Tothis coordinate (1), and necessaryand solutionof (1). We usethemodeltrainedusing MixMatch [5] under 3 cases: (1) l = 100, u =1 , (2) = l = u = 100(reverse) and (3) = 100.