Summarize the key points about the challenges of summarization described in this text:

Automatic text summarization faces several challenges, primarily due to the complex nature of human language and the inherent ambiguity in interpreting and representing meaning. One major challenge is identifying and extracting the most salient and relevant information from the source text, which requires a deep understanding of the context, semantics, and discourse structure. Another difficulty lies in generating coherent and fluent summaries that accurately convey the key points while avoiding redundancy or contradictions. Additionally, summarization systems must handle various linguistic phenomena, such as anaphora resolution, paraphrasing, and lexical simplification. Furthermore, developing robust summarization models that can generalize across different domains and text genres is a significant challenge. Overall, the complexities of natural language understanding and generation, along with the subjective nature of what constitutes a 'good' summary, make automatic text summarization a formidable task in the field of natural language processing.
Summarize the key points about the challenges of summarization described in this text:

Automatic text summarization faces several challenges, primarily due to the complex nature of human language and the inherent ambiguity in interpreting and representing meaning. One major challenge is identifying and extracting the most salient and relevant information from the source text, which requires a deep understanding of the context, semantics, and discourse structure. Another difficulty lies in generating coherent and fluent summaries that accurately convey the key points while avoiding redundancy or contradictions. Additionally, summarization systems must handle various linguistic phenomena, such as anaphora resolution, paraphrasing, and lexical simplification. Furthermore, developing robust summarization models that can generalize across different domains and text genres is a significant challenge. Overall, the complexities of natural language understanding and generation, along with the subjective nature of what constitutes a 'good' summary, make automatic text summarization a formidable task in the field of natural language processing.
user
The key challenges in automatic text summarization include identifying and extracting the most salient information from the source text, generating coherent and fluent summaries that accurately convey the main points, handling linguistic phenomena like anaphora resolution and paraphrasing, and developing robust models that can generalize across different domains and text genres. The inherent ambiguity in interpreting meaning and the subjective nature of what constitutes a good summary also contribute to the difficulty of this task.
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: 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.
