Linear Probe Interpretability. Moreover, these probes cannot affect the training phase of a model,

Moreover, these probes cannot affect the training phase of a model, and they are generally added after training. Learn about the construction, utilization, and insights gained from linear probes, alongside their limitations and challenges. Recent work has used linear probes, lightweight tools for analyzing model representations, to study various LLM skills such as the ability to model user sentiment and political perspective. Interpretability Of course, SAEs were created for interpretability research, and we find that some of the most interesting applications of SAE probes are in providing interpretability insight. So I combined them. This is basically linear probes that constrain the amount of neurons of the probe. Supporting automated checks—cosine alignment, adversarial fragment tests, and causal probes—ran on the same cloud TPU pod used for training. We train simple linear residual stream probes on the (in-domain) training dataset we also use for finding the SAE features. We use our framework to complement previous findings on the inner mechanisms of ViTs. Given a model M trained on the main task (e.

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