Glossary · Term

capability spillover

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Definition

Plain language

When a tool built partly from a skilled AI quietly transfers some of that skill into a weaker model that was never trained for it.

As stated in the literature

An observed effect where passing a frozen base model's activations through a jointly-trained crosscoder injects an RL-trained capability (e.g., tool selection) into it via shared decoder directions; the semantic intent leaks while the exact surface-form template stays private to the trained model.

Why it matters: It shows that skills can leak between models through shared internal machinery, which matters both for cheaply boosting weak models and for spotting unintended capability transfer.

For example, a weaker model that was never trained to pick the right tool starts choosing tools well once its internal signals are routed through a component built from a more skilled model.

Heard on the show

“That's capability spillover.”
Episode 175 — One Crosscoder Feature Flips a Stalling Chatbot Into a Working Agent

Mentioned in 1 episode

  1. 175
    One Crosscoder Feature Flips a Stalling Chatbot Into a Working Agent

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