Summarize the following text in a single concise sentence: Automatic text summarization has become an increasingly important task in the era of information overload, as it helps users navigate and understand large volumes of textual data more efficiently. Various approaches have been developed, ranging from traditional rule-based and statistical methods to more recent deep learning techniques that leverage neural networks and transformers. While extractive methods identify and extract the most salient sentences or phrases from the original text, abstractive approaches generate entirely new summaries by interpreting and rephrasing the content, often producing more concise and coherent results. Despite ongoing challenges, such as preserving factual accuracy and capturing context, text summarization remains a vital area of research with numerous applications in fields like news aggregation, scientific literature analysis, and customer service.
Summarize the following text in a single concise sentence: Automatic text summarization has become an increasingly important task in the era of information overload, as it helps users navigate and understand large volumes of textual data more efficiently. Various approaches have been developed, ranging from traditional rule-based and statistical methods to more recent deep learning techniques that leverage neural networks and transformers. While extractive methods identify and extract the most salient sentences or phrases from the original text, abstractive approaches generate entirely new summaries by interpreting and rephrasing the content, often producing more concise and coherent results. Despite ongoing challenges, such as preserving factual accuracy and capturing context, text summarization remains a vital area of research with numerous applications in fields like news aggregation, scientific literature analysis, and customer service.
user
Automatic text summarization techniques, ranging from traditional rule-based and statistical methods to deep learning approaches, aim to efficiently condense large volumes of textual data into concise summaries, either by extracting salient sentences or abstractively generating new content, with applications in various fields despite ongoing challenges.
assistant
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: What does this text say in one sentence?

Onceropyga pulchra is a species of moth in the family Zygaenidae. It is found in Australia in south-eastern Queensland and eastern New South Wales.[1]

The length of the forewings is 6.5 mm for males and 8 mm for females. The upperside of the forewings is dark brown with a slightly lighter spot at the end of the cell, distally bordered by a suffusion of blackish scales. The underside is dark grey brown, but slightly lighter medially. The hindwings are blackish on both sides, but slightly lighter basally, with a light brown costal margin.[1]
Response: Onceropyga pulchra, a species of moth found in south-eastern and eastern Australia, has wings between 6.5-8mm in length, is dark and lighter brown with blackish scales on the upperside and dark grey-brown and blackish coloring on the underside.

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.
