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circuit-removability

topic1 events
papersSEP 10 04:00 UTC

Training trajectories determine circuit removability in annealable soft-prior Transformers

Researchers asked whether retrieval circuits that small Transformers learn with the help of soft positional priors keep functioning once that prior is taken away. They tested this using a model whose prior-based attention biases can be gradually annealed out during training. The results indicate that the specific training trajectory, not just the architecture, decides whether a learned circuit can stand on its own after the prior is removed.

interpretability/transformers/training-dynamics/retrieval