In two Transformer-based L2 speaking graders, a concept's linear recoverability in a hidden layer does not predict its influence on the predicted score, and sparse-autoencoder probing attenuates measured sensitivity.
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Bias Analysis of L2 Speaking Assessment Systems Using Concept Activation Vectors
In two Transformer-based L2 speaking graders, a concept's linear recoverability in a hidden layer does not predict its influence on the predicted score, and sparse-autoencoder probing attenuates measured sensitivity.