In RAG tasks, we often encounter complex questions that require in-depth analysis and the gathering of information from various sources. This is where decomposition comes into play. Decomposition is a powerful technique that breaks down a large, intricate problem into smaller, more manageable sub-problems. By addressing these sub-problems independently, we can simplify the overall task and ultimately create a more comprehensive and accurate response.

What is decomposition?

In the context of RAG, decomposition involves dividing a primary question into a series of smaller, more focused sub-questions. Each sub-question can be answered independently, and the answers are then combined to form a comprehensive response to the original question. This approach offers several advantages:

  • Enhanced efficiency: By tackling smaller sub-problems, the retrieval and generation processes become more efficient as the system focuses on specific aspects of the main question.

  • Improved accuracy: Decomposing the question allows for a deeper exploration of each sub-question, potentially leading to more accurate and relevant answers.

  • Structured response: Decomposition facilitates the organization of the final answer by presenting the sub-questions and their corresponding answers in a clear, structured format.

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