Papers with multiclass log-linear model

1 papers
Log-linear Guardedness and its Implications (2023.acl-long)

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Challenge: Existing methods for erasing human-interpretable concepts from neural representations that assume linearity are not fully understood.
Approach: They define linear guardedness as the inability of an adversary to predict the concept directly from the representation . they show that a log-linear model can be constructed that indirectly recovers the concept .
Outcome: The proposed model can be constructed that indirectly recovers the erased concept in some cases.

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