A quick Google search of probe tuning doesn’t turn up anything. Do you have more info on it?
Probe-tuning doesn’t train on LLM’s own “original rollouts” at all, only on LLM’s activations during the context pass through the LLM.
This sounds like regular fine tuning to me. Unless you mean that the loss is calculated based on one (multiple?) of the network’s activations rather than on the output logits.
Edit: I think I get what you mean now. You want to hook a probe to a model and fine-tune it to perform well as a probe classifier, right?
I think I get what you mean now. You want to hook a probe to a model and fine-tune it to perform well as a probe classifier, right?
Yes, exactly. Also I came up with “probe-tuning” myself, maybe not a good name, but anyways I was trying to find something on Scholar in this direction.
A quick Google search of probe tuning doesn’t turn up anything. Do you have more info on it?
This sounds like regular fine tuning to me. Unless you mean that the loss is calculated based on one (multiple?) of the network’s activations rather than on the output logits.
Edit: I think I get what you mean now. You want to hook a probe to a model and fine-tune it to perform well as a probe classifier, right?
Yes, exactly. Also I came up with “probe-tuning” myself, maybe not a good name, but anyways I was trying to find something on Scholar in this direction.