Paper: Agents Can Learn In-Context Without Human Data

A new paper by KWantlin introduces a method where AI agents can learn in-context without any human data. The core mechanism involves agents imagining and practicing goals to infer intent from behaviors, which they can then apply during testing by observing action sequences.

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