SFT on weak demonstrations followed by RL elicits full performance from sandbagging LLMs, but only when training and deployment are indistinguishable to the model.
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Removing Sandbagging in LLMs by Training with Weak Supervision
SFT on weak demonstrations followed by RL elicits full performance from sandbagging LLMs, but only when training and deployment are indistinguishable to the model.