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 following text about the future trends and research directions in text summarization:

Text summarization is an active area of research, and there are several exciting trends and future directions that are shaping the field. Some of the key trends and research directions include:

1. Neural network approaches: The application of deep learning and neural network models, such as transformer architectures and attention mechanisms, has shown promising results in text summarization. These approaches can capture complex semantic relationships and generate more coherent and natural-sounding summaries.

2. Multimodal summarization: Extending summarization techniques to handle multimodal data, such as text combined with images, videos, or audio, is an emerging area of research. Multimodal summarization aims to generate summaries that integrate information from multiple modalities, providing a more comprehensive and contextual understanding.

3. Personalized and query-focused summarization: Developing summarization systems that can generate personalized summaries tailored to individual user preferences, interests, or queries is a growing research area. This involves incorporating user modeling and adapting summaries based on context and user needs.

4. Abstractive summarization: While extractive summarization has been widely studied, there is increasing interest in developing more advanced abstractive summarization techniques that can generate coherent and fluent summaries without relying solely on extracting sentences from the original text.

5. Explainable and controllable summarization: Improving the interpretability and controllability of summarization systems is an important research direction. This includes developing models that can provide explanations for their summarization decisions and allow users to control or fine-tune the summary generation process based on specific requirements or preferences.

6. Multilingual and cross-lingual summarization: Extending summarization capabilities to handle multiple languages and generating summaries across different languages is a challenging area of research, with potential applications in various domains, such as global news reporting and cross-cultural communication.

As text summarization techniques continue to advance, they are expected to play an increasingly important role in extracting insights from vast amounts of data and facilitating efficient information processing and knowledge acquisition across various domains.
user
The text discusses future trends and research directions in text summarization, including the application of neural network approaches and deep learning models, multimodal summarization handling text with other modalities like images or videos, personalized and query-focused summarization tailored to user needs, advanced abstractive summarization techniques for generating coherent summaries, explainable and controllable summarization systems, and multilingual and cross-lingual summarization capabilities. These developments aim to improve the effectiveness, interpretability, and versatility of summarization systems, enabling efficient information processing and knowledge acquisition from large amounts of data across various domains.
assistant