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 the main points in the text below - 

You'll always want to have access to sufficient emergency funds for, well, emergencies. Make sure you can afford a health emergency (some insurance plans require you to pay first and claim for reimbursement later), a one-way ticket home in the event that something urgent happens, a missed flight, or a theft or unexpected mishap. And, more practically, you may find that you've under-budgeted and you need to increase your budget a bit while you're on the road, so having access to some emergency cash might prevent you from having to cut your trip short or miss out on things you wanted to see.

In short, you need to be able to afford to get yourself out of bad situations if you really have to. Remember that as a solo traveler you will generally not have another person readily available to help with bad situations, so it's up to you to be able to manage them.

It's a good idea to have a variety of different sources of emergency funds, including cash in hard currencies like US dollars or Euros, a credit card (and backup) with a decent limit, and a trusted friend or relative back home who can send you money in an emergency.
Response: - Have money set aside for emergencies like health issues or an emergency trip home
- Budget enough to get yourself out of unexpected situations if needed
- Remember, if you’re by yourself you will be the one managing any problems
- Carry a few different ways to pay for things if needed like cash and credit cards, and  have someone to borrow from back home if needed

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 main points covered in the following text about text summarization:

Text summarization is a fundamental task in natural language processing that aims to condense the most salient information from a source document into a concise and coherent summary. This process involves analyzing the semantic content, identifying the key topics and central ideas, and synthesizing this information into a compact representation while preserving the overall meaning and context. There are two primary approaches to text summarization: extractive and abstractive. Extractive summarization methods work by selecting and concatenating the most relevant sentences or text segments from the original document to form the summary. These methods leverage techniques such as sentence scoring, graph-based ranking, and integer linear programming to identify the most informative sentences. On the other hand, abstractive summarization techniques generate novel sentences that capture the essential information from the source text, often using advanced natural language generation models like sequence-to-sequence architectures or graph transformations. Abstractive approaches have the potential to produce more concise and coherent summaries, but are generally more complex and computationally expensive. Regardless of the approach, evaluation of summarization systems remains a challenge, with metrics like ROUGE and question-answering performance serving as proxies for assessing summary quality and informativeness. Current research efforts focus on improving context modeling, handling long-range dependencies, increasing factual consistency, and developing more robust evaluation protocols.
user
- Text summarization condenses the most important information from a source document into a concise summary
- It involves analyzing semantic content, identifying key topics/ideas, and synthesizing information while preserving meaning and context
- There are two main approaches: extractive (selecting and concatenating relevant sentences/text spans) and abstractive (generating novel sentences)
- Extractive uses techniques like sentence scoring, graph ranking, integer programming to identify informative sentences
- Abstractive leverages advanced language models (seq2seq, graph transformations) to generate new sentences capturing essential information
- Abstractive has potential for more concise, coherent summaries but is more complex
- Evaluation uses metrics like ROUGE, question-answering as proxies for quality/informativeness
- Research focuses on improving context, long-range dependencies, factual consistency, robust evaluation
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