Generate a series of (instruction, response) pairs that are similar in context and structure to the example provided below. Each pair should consist of a concise instruction followed by an appropriate, detailed response. The instruction should pose a clear task or question, while the response should provide a comprehensive answer or solution that could be understood by someone with a basic understanding of the subject.

Example pair: 
Instruction: In short, what does this paragraph say about cleansers? Here is the text:
A mild cleanser: When selecting a cleanser, choose one for your skin type. Dr. Katta says, “For example, if you have acne-prone skin, use a mild cleanser that removes oil.” Dry skin does better with a hydrating cleanser.

To get the best results from your cleanser, wash your face twice a day – when you get up and before bed. You also want to wash after sweating.
Response: It says to choose a cleanser based on your skin type and to wash your face before and after bed and after sweating.

Your task is to generate more pairs that maintain this level of clarity and detail. The topic is Summarization. Write a long text of instruction by yourself, then summarize the given instruction in a response. Ensure that the responses are informative and accurate, suitable for an educational context. 

Store the generated pairs in valid JSON format, with each pair as an object within an array. Each object should have two key-value pairs: "instruction" and "response". For instance: 

{"contents": [{"instruction": "text", "response": "text"}, {"instruction": "text", "response": "text"}, ...]} 

Remember to maintain consistency in the format and ensure the generated pairs are diverse and cover a broad range of subjects. You must return the response in the asked format and you must not add any additional text in your response.

Summarize the key ideas about using summarization for question answering from the following text:

Text summarization can be a valuable tool for question answering systems. By condensing large amounts of text into concise summaries, summarization techniques can help extract the most relevant information needed to answer a given question. One approach is to generate summaries specifically tailored to the question at hand, focusing on extracting and synthesizing information relevant to the query. This can be achieved by incorporating the question into the summarization model's input or by using question-guided attention mechanisms. Another approach is to first generate a general summary of the text and then use this summary as the input for a separate question answering module. This can be more computationally efficient than processing the entire text for each question. Additionally, multi-document summarization techniques can be used to consolidate information from multiple sources, which can be particularly useful for complex queries that require information from diverse documents.
user
The key ideas about using summarization for question answering are: 1) Summaries can extract relevant information to answer questions from large texts. 2) Generating question-specific summaries using the question as input or question-guided attention. 3) Using general summaries as input to a separate question answering module for efficiency. 4) Multi-document summarization to consolidate information from multiple sources for complex queries.
assistant