Learning to Decide, Not to Reason: Parameter-Efficient Decision Operators via Low-Rank Activation Steering
Injecting skills into a frozen language model currently costs a million parameters and a reinforcement-learning pipeline. We introduce \method{}, a System-1 decision operator trained by behavior cloning that lowers this cost by roughly two orders of magnitude.
By Ran Li, Lei ChenarXiv cs.LG
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Originally published by arXiv cs.LG on Oct 7, 2026.
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