Description

Long-range dependency refers to the ability of a model to capture and utilize information from distant parts of an input sequence. In natural language processing, this is crucial for understanding context, resolving references, and maintaining coherence over long passages of text. Traditional recurrent neural networks often struggle with long-range dependencies due to the vanishing gradient problem, which led to the development of architectures like LSTMs and Transformers that are better equipped to handle these dependencies.

Examples

• 👥 Understanding pronoun references across paragraphs
• 📚 Maintaining plot consistency in long-form text generation

Applications