Abstract: A method for poetry generation includes receiving generation information indicative of a theme for the poetry generation, and determining at least a candidate piece of poetry corresponding to the generation information according to an autoregressive language model that is configured to generate elements in the candidate piece of poetry in an autoregressive manner with a plurality of regression rounds. An element in the elements is a character or a word. The autoregressive language model is configured for generating poetry in a plurality of formats, the autoregressive language model includes a plurality of processing layers connected sequentially, a processing layer in the plurality of processing layers is configured to determine attention levels for potential elements in a potential element list according to generated elements prior to a current regression round, and predict one or more additional element for the current regression round using a neural network according to the attention levels.