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: Read the following: 

If a Spanish class were to go on an in-country immersion in Spain, they’d be flooded by the sights and sounds of native speakers going about their business. Good times! But that would make a huge dent in everybody’s budget. So why not bring a native speaker to class instead?

Pick somebody who’s outgoing, a natural extrovert who loves interacting with people and doesn’t take himself too seriously. Ask him to prepare a short talk. And he can really talk about anything—so long as he does it in Spanish. He can tell his personal story, talk about his job or share some interesting quirk about his culture.

You may be a native speaker yourself, but count yourself out. Bring some new face to stand in front of the class. (There’s just something more effective about a fresh face.)

Now, please summarize what it says about having a native speaker visit the classroom.
Response: Bringing a native speaker into the classroom can help immerse students in a foreign language. Invite a guest speaker who is outgoing, extroverted, and has something interesting to share. 

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.

Read the following text and summarize the main ideas related to summarizing academic papers:

Academic papers, such as research articles and conference proceedings, are rich sources of information but can be dense and lengthy. Summarizing these papers is crucial for researchers to quickly grasp the key contributions, methodologies, and findings without having to read through the entire document. Effective summarization of academic papers requires a deep understanding of the domain-specific terminology, concepts, and conventions. Additionally, capturing the logical flow of ideas, recognizing the paper's structure (e.g., abstract, introduction, methods, results, discussion), and identifying the novel contributions are essential. Several approaches have been proposed, including extractive methods that select and concatenate relevant sentences, and abstractive methods that generate new sentences using natural language generation techniques. Incorporating citation networks, understanding mathematical equations and figures, and handling complex terminology are some of the challenges in this domain.
user
The text discusses summarizing academic papers, such as research articles and conference proceedings, which are rich but dense sources of information. Summarizing academic papers is important for researchers to quickly understand the key contributions, methodologies, and findings without reading the entire document. Effective summarization requires understanding domain-specific terminology, concepts, and conventions, capturing the logical flow of ideas, recognizing the paper's structure, and identifying novel contributions. Approaches include extractive methods that select and concatenate relevant sentences, and abstractive methods that generate new sentences using natural language generation techniques. Challenges include incorporating citation networks, understanding mathematical equations and figures, and handling complex terminology.
assistant