Uncertainty-aware sequence modeling

Abstract

Described herein are systems and methods for improving accuracy of model output generation. A method can include obtaining a risk-aware model and a user input, applying the risk-aware model to the user input, receiving, based on the applying, model output and corresponding risk values, comparing the corresponding risk values to a threshold risk value, and regenerating the user input based on the comparing. The method can also include iteratively performing the applying, receiving, comparing, and regenerating using the regenerated user input until one or more processing conditions is met. The user input can be regenerated in response to determining that the corresponding risk values are greater than the threshold risk value. The model output can include one or more sequences in a train-of-thought (TOT) of the risk-aware model.