Expression Generation
Expression generation focuses on automatically creating textual or visual representations of concepts, emotions, or mathematical expressions. Current research emphasizes improving the accuracy and contextual appropriateness of generated expressions, exploring model architectures like transformers and generative adversarial networks (GANs), and investigating the interplay between generation and comprehension tasks. This field is significant for advancing natural language processing, computer vision, and scientific discovery by enabling more natural human-computer interaction, facilitating data augmentation, and automating complex symbolic reasoning tasks.
Papers
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