Textual Context

Textual context research focuses on improving the understanding and utilization of surrounding text to enhance various natural language processing tasks. Current efforts concentrate on incorporating contextual information into models through techniques like hyper-prompting, heterogeneous graph convolutional networks for relation rectification, and context-aware encoders in machine translation and speech recognition. This research is significant because effectively leveraging textual context is crucial for improving the accuracy and naturalness of machine-generated text, images, and speech, leading to advancements in applications such as machine translation, text-to-speech, and text-to-image generation.