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This category of long sequence modeling focuses on tasks where a language model's output is an extensive sequence of text, often generated from a brief initial input. Using the text generation probability notation $$\Pr(\mathbf{y}|\mathbf{x})$$, this describes scenarios where the generated text $$\mathbf{y}$$ is a long sequence.

Long Text Generation

An illustrative example of long text generation is the task of creating a lengthy story based on a few keywords. In this case, the model takes a concise input (the keywords) and produces an extensive, coherent narrative as the output.

Example of Long Text Generation: Story Generation

Analyze the following scenario and explain why it represents a modeling problem where the primary challenge is generating an extensive output from a concise input.

Marketing AI Tool Scenario

Match each task description with the symbolic representation that best describes the relationship between the input length (represented by 'x') and the output length (represented by 'y').

A developer is building a system that needs to perform a specific text-based task. Which of the following tasks best represents a scenario where the model must generate an extensive and detailed output based on a very brief initial input?

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