Summarize the following text about the challenges and future directions in text summarization research:

While significant progress has been made in text summarization, numerous challenges and research directions remain to be explored:

1. Contextual and domain-specific summarization: Developing summarization models that can effectively capture and incorporate context, domain knowledge, and background information to generate more relevant and tailored summaries.

2. Multi-modal summarization: Extending summarization techniques to handle multi-modal inputs, such as text combined with images, videos, or audio, to generate comprehensive summaries that leverage information from multiple modalities.

3. Unsupervised and few-shot learning: Exploring unsupervised and few-shot learning approaches to reduce the reliance on large-scale annotated datasets, enabling more efficient and adaptable summarization models.

4. Explainable and controllable summarization: Enhancing the interpretability and controllability of summarization systems, allowing users to understand the reasoning behind generated summaries and exert more control over the summarization process.

5. Multilingual and cross-lingual summarization: Developing summarization techniques that can handle multiple languages and generate summaries across different languages, enabling more widespread accessibility and information sharing.

6. Evaluation and benchmarking: Continuously refining evaluation metrics and benchmarking frameworks to more accurately assess the quality and performance of summarization systems, accounting for diverse user needs and application contexts.
Summarize the following text about the challenges and future directions in text summarization research:

While significant progress has been made in text summarization, numerous challenges and research directions remain to be explored:

1. Contextual and domain-specific summarization: Developing summarization models that can effectively capture and incorporate context, domain knowledge, and background information to generate more relevant and tailored summaries.

2. Multi-modal summarization: Extending summarization techniques to handle multi-modal inputs, such as text combined with images, videos, or audio, to generate comprehensive summaries that leverage information from multiple modalities.

3. Unsupervised and few-shot learning: Exploring unsupervised and few-shot learning approaches to reduce the reliance on large-scale annotated datasets, enabling more efficient and adaptable summarization models.

4. Explainable and controllable summarization: Enhancing the interpretability and controllability of summarization systems, allowing users to understand the reasoning behind generated summaries and exert more control over the summarization process.

5. Multilingual and cross-lingual summarization: Developing summarization techniques that can handle multiple languages and generate summaries across different languages, enabling more widespread accessibility and information sharing.

6. Evaluation and benchmarking: Continuously refining evaluation metrics and benchmarking frameworks to more accurately assess the quality and performance of summarization systems, accounting for diverse user needs and application contexts.
user
Future directions in text summarization research include contextual and domain-specific summarization, multi-modal summarization handling text with other modalities, unsupervised and few-shot learning approaches, explainable and controllable summarization systems, multilingual and cross-lingual summarization capabilities, and continuous refinement of evaluation metrics and benchmarking frameworks. Addressing these challenges aims to enhance the relevance, accessibility, and performance of summarization technologies across diverse domains and applications.
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 are Iron Man's powers? Draw your answer from the text below:

Without his suit of armor, Tony Stark has no supernatural powers. He is only limited by his imagination. Tony is a brilliant engineer and has used his talents to create a powerful suit of armor that enables the wearer to fly, shoot beams of energy from his hands and chest, and resist the vacuum of space. The suit also protects the wearer from damage and grants superhuman strength.

The suit is constantly being redesigned to face the new challenges that Tony Stark meets on a daily basis. There are specialty suits that have been made such as the Arctic, Stealth, Space, Hulkbuster, and Thorbuster armors. There have been nearly 40 different variations of the Iron Man armor in the current reality of the Iron Man comics.
Response: In short, Iron Man has no real superpowers outside his suit. Instead, he uses his engineering skillset to create armor that grants extreme strength, flight and energy beams. His suit also protects him from damage and he regularly upgrades it to meet his needs.

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.
