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 information about retinoids. Here is the information:
Retinoid: The term "retinoid" is a catch-all for an array of vitamin A-based products used on skin. It can treat mild fine lines and wrinkles, acne, and dark spots. It can also improve skin texture.

If you’re looking to treat uneven skin tone, dark spots, or your skin’s texture, look for the word “retinol.” It’s a type of retinoid that’s used for these purposes.

Retinol can give you younger-looking skin by speeding up new skin cell turnover, which starts to slow in your 20s.

To treat acne, dermatologists prescribe one of these retinoids – adapalene, tazarotene, tretinoin, or trifarotene. You’ll also find adapalene in an acne-fighting product available without a prescription.

When spread on acne-prone skin, a retinoid can unclog pores. This can give you clearer skin and allow other acne gels and creams to work better.

When to apply a retinoid: Dr. Baxt recommends applying a retinoid before bed. After washing your face, wait 20 to 30 minutes and then apply it.

If you find the retinoid too drying, apply a moisturizer immediately after washing your face, using a moisturizer that won’t clog your pores. Then apply the retinoid 20 to 30 minutes later.
Response: Retinoids are vitamin A-based products. They have been found to treat mild fine lines, acne, wrinkles, and dark spots and improve skin texture. Apply retinoids 20 to 30 minutes after washing your face before bed.

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 following information about challenges and considerations in summarization:

Summarization is a challenging task due to several factors:

1. Language complexity: Natural language is inherently complex, with ambiguities, idioms, and context-dependent meanings. Understanding and capturing the nuances of language is difficult for automated systems.

2. Domain-specific knowledge: Effective summarization often requires domain-specific knowledge and understanding of the subject matter, which can be challenging to incorporate into general-purpose summarization models.

3. Coherence and cohesion: Generating coherent and cohesive summaries that maintain the logical flow and relationships between ideas is a significant challenge, particularly for abstractive summarization.

4. Information redundancy and contradiction: Identifying and resolving redundant or contradictory information in the input text is necessary for producing consistent and concise summaries.

5. Evaluation challenges: Evaluating the quality of summaries is a complex task, as it may involve subjective judgments and context-dependent factors. Automated evaluation metrics like ROUGE may not fully capture the nuances of human-level summarization quality.

When developing or using summarization systems, it is important to consider factors such as the target domain, the desired level of abstraction (extractive or abstractive), the trade-off between summary length and informativeness, and the availability of high-quality training data. Additionally, ethical considerations, such as potential biases in the training data or the model, and the appropriate use of summarization technology, should be taken into account.
user
The text discusses several challenges and considerations in summarization, including the complexity of natural language, the need for domain-specific knowledge, maintaining coherence and cohesion in summaries, handling information redundancy and contradictions, and the difficulty of evaluating summary quality. Other important factors to consider are the target domain, desired level of abstraction (extractive or abstractive), trade-off between summary length and informativeness, availability of training data, and ethical considerations such as potential biases and appropriate use of the technology.
assistant