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Welfare, Improvability, and Variance: A Principal-Agent Approach to Optimal Benchmark Item Aggregation
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A Negative Result on Cross-Model Activation Transfer in a Pythia Multi-Hop Setting
Announce Type: new Abstract: Recent work shows that language models can transmit behavioural traits through hidden signals in generated data during training. We ask whether a more direct and stricter channel is also viable: can one language model communicate useful intermediate reasoning state to another at inference time by translating and injecting hidden activations, rather than by passing natural-language text?
A Negative Result on Cross-Model Activation Transfer in a Pythia Multi-Hop Setting
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