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: Summarize this post in less than 4 sentences. Use the text following this request. 


Your health is what you eat
Research has consistently shown that the Mediterranean diet and other whole food diets are associated with better health and longer lives, and ultraprocessed foods and drinks like soda, chips and fast food, among others, are linked with poor health outcomes such as diabetes, cardiovascular disease, cancer and other diseases.

But improving the diet of an individual, let alone a population, is challenging. Whole foods are sometimes less convenient and less tasty for modern lifestyles and preferences. Furthermore, food processing can be beneficial by preventing spoilage and extending shelf life. Whole grain processing in particular extends shelf life by removing the germ and bran that otherwise rapidly spoil. Long-term storage of affordable calories has helped address food insecurity, a primary challenge in public health.

Only 5% of the U.S. population gets sufficient fiber, a prebiotic nutrient linked to metabolic, immune and neurologic health. Americans are likely also deficient in phytonutrients, potassium and certain healthy fats linked to lower rates of cardiovascular disease and cancer.
Response: While research has shown that Mediterranean diets and others with plenty of whole foods are associated with longer, healthier lives, switching to these diets from diets with a lot of heavily processed foods can be difficult. This goes beyond the individual difficulty as processed foods last longer than whole foods, they often taste better, and they're usually more affordable. Affordable food that can last a long time is key in addressing food insecurity, but only a very small portion of the United States population gets enough fiber and other nutrients.

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.

Write a concise summary that captures the main ideas of the following text about summarization techniques:

Text summarization is the process of creating a concise and accurate summary of a longer text document. There are two main approaches to text summarization: extractive and abstractive. Extractive summarization involves selecting and combining the most important sentences or phrases from the original text to form the summary. This method preserves the original wording and can be more accurate, but may lack coherence. Abstractive summarization, on the other hand, aims to generate a new, coherent summary that captures the main ideas in natural language. This approach requires deeper language understanding and generation capabilities. Recent advances in natural language processing, particularly with deep learning models like transformer architectures, have improved the quality of abstractive summaries. However, extractive methods are still widely used due to their simplicity and robustness. Evaluation of text summaries can be challenging, often relying on metrics like ROUGE that measure overlap with human-generated reference summaries or ratings from human evaluators. The ideal summarization technique depends on the specific use case and requirements for accuracy, coherence, and efficiency.
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Text summarization involves creating a concise summary from a longer document, typically using either extractive or abstractive methods. Extractive summarization selects and combines important sentences from the original text, while abstractive summarization generates a new summary that captures the main ideas in natural language. Recent advances in deep learning have improved abstractive summarization quality, but extractive methods are still widely used due to their simplicity. Evaluation of summaries can be challenging, often relying on overlap metrics or human ratings.
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