This AI Paper Unlocks the Secret of In-Context Learning: How Language Models Encode Functions into Vector Magic

In autoregressive transformer language models, a neural mechanism is identified that represents an input-output function as a compact vector known as a function vector (FV). Causal mediation analysis is applied to diverse in-context-learning tasks, revealing that a small number of attention heads transport FVs, which remain robust across various contexts, enabling task execution in zero-shot […]

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