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[image]a model must “choose” two words from a set at random (given a random seed) and have an output distribution with probabilities 70% and 30% respectively over these two words.
- If a model was pretrained on transcripts from this task, we expect it would have an output distribution that is uniform over the set of words, rather than concentrated on just two words.
- To succeed at the task, the model must follow the instructions exactly, understand them as referring to itself, and “control” its own logits to avoid imitating pretraining data
- Will a pre-2028 LLM be demonstrate a success rate of over 50% on this ANTI-IMITATION-OUTPUT-CONTROL task? We will only count performance on the "not-given" split of this task.
- See page 95 of the paper pdf for more details.
- Models will be evaluated as in the paper.
