Suppose your generative model needs to process very long inputs that exceed typical context limits. How would you approach managing or compressing that information effectively?

Focus on outlining specific techniques for managing and compressing long inputs for generative models. Discuss methods such as chunking the input data into manageable segments, summarization techniques to distill key information, and the use of hierarchical models to maintain context. Consider mentioning advanced strategies like attention mechanisms or embedding techniques that help retain important features while reducing input size. Be prepared to justify your choices based on their impact on model performance and the trade-offs involved in each approach.