Pre-training a transformer on data generated by randomly initialized LSTMs yields zero-shot in-context learning on several held-out datasets, with gains that improve with scale and faster finetuning.
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Universal pre-training by iterated random computation
Pre-training a transformer on data generated by randomly initialized LSTMs yields zero-shot in-context learning on several held-out datasets, with gains that improve with scale and faster finetuning.