Summarization with Large Language Models

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Summarization models can be categorized into two types: extractive models and abstractive models. Extractive models, as the name implies, do not generate new text but rather identify and reproduce important sections of the original text verbatim.

Extractive summarizers undertake three key tasks.

1. Constructing Intermediate Representation: Initially, they construct an intermediate representation of the input text, aiming to encapsulate its main aspects.
2. Scoring Sentences: Following the construction of the intermediate representation, sentences are scored based on their relevance to the main aspects captured.
3. Selecting Top-Scoring Sentences: Once sentences are scored, the algorithm selects a summary by choosing a specific number of sentences with the highest scores.

I. Techniques for Intermediate Representation: Various techniques can be employed to generate the intermediate representation of the input text. This representation serves as the basis for identifying important portions of the…