Abstract: In view of the need to improve text generation technology, embodiments described herein provide a neural network model that generates a text output with constraints to achieve desired output behavior, such as reduced toxicity or hallucinations, and inclusion of certain keywords.

Abstract: Embodiments described herein provide a method of training a language model by tuning a prompt. The method comprises masking tokens of first and second conversational texts which have the same semantic meaning but in different languages (e.g., a translation). The masked texts are input to a language model with a prepended soft prompt. The language model generates respective predicted outputs. A loss objective is computed including a masked language model loss. The prompt is updated based on the computed loss objective via backpropagation while keeping the language model frozen.