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 2-3 sentences, summarize these paragraphs about the Shanghai Dragons.

Here are the paragraphs I'm referring to.

Around this time last year, the professional Overwatch team Shanghai Dragons had just finished up a history-making 0-40 season. At the time, nobody would have expected that just one year later they’d be leaving the league’s top three teams in a heap of black-and-blue bodies on the ground. Maybe they should change their name to the Shanghai Phoenixes.

Overwatch League season two’s third stage culminated in a mini-tournament over the weekend with hundreds of thousands of dollars on the line. Shanghai Dragons came out on top. They had the hardest possible path to this championship: They barely made it into the stage finals as the eighth seed, and then they took out the league’s three best teams—New York Excelsior, Vancouver Titans, and San Francisco Shock—back to back to back.
Response: Last season, the Shanghai Dragons finished a shockingly awful 0-40 season. This year, the Dragons just won a mini-tournament against some of the league's top teams. The Dragons entered the stage finals as the eighth seed before knocking out the Excelsior, Titans, and Shock in three straight games.

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 key points covered in the following text about the challenges and future directions for summarization research:

Despite significant recent advancements, summarization remains a highly challenging problem in natural language processing. One key obstacle is accounting for the full context and meaning of the source text, which can be difficult for current models to capture. Additionally, existing systems often struggle with consistency, coherence, and factual accuracy when generating abstractive summaries. Another challenge lies in adapting summarization models to handle diverse domains, genres, and languages beyond the news articles commonly used for training data. Issues like length control, handling multiple input documents, and summarizing multimodal data like text combined with images or videos also present difficulties. From a human-centric perspective, controlling for desired summary attributes like focus, tone, and level of detail is an open research area. Looking ahead, more robust evaluation methodologies, interpretability techniques for analyzing model behavior, and techniques for few-shot or unsupervised adaptation could drive further progress in summarization.
user
Summarization remains challenging due to difficulties in fully capturing context and meaning, maintaining consistency and accuracy in abstractive summaries, and adapting to diverse domains and genres. Other key challenges include length control, multi-document and multimodal summarization, and controlling for desired summary attributes. Future directions involve developing robust evaluation methods, improving model interpretability, and enabling few-shot or unsupervised adaptation. Overcoming these obstacles could drive further advancements in the field.
assistant