Summarize the following text describing the challenges and future directions of summarization: Summarization systems face several challenges, including handling complex discourse structures, maintaining factual consistency, and capturing nuanced semantic information. Existing techniques often struggle with long-range dependencies, anaphora resolution, and generating coherent, non-redundant summaries. Additionally, summarizing diverse data sources like multimedia content, scientific literature, and conversational data poses unique challenges. Future research directions include developing more robust language models, improving abstractive summarization capabilities, and exploring transfer learning and few-shot learning approaches to adapt summarization models to new domains. Incorporating commonsense reasoning, knowledge graphs, and multimodal information can also enhance summarization performance. Ultimately, the goal is to create human-like summarization systems that can understand and distill information effectively across various contexts and domains.
Summarize the following text describing the challenges and future directions of summarization: Summarization systems face several challenges, including handling complex discourse structures, maintaining factual consistency, and capturing nuanced semantic information. Existing techniques often struggle with long-range dependencies, anaphora resolution, and generating coherent, non-redundant summaries. Additionally, summarizing diverse data sources like multimedia content, scientific literature, and conversational data poses unique challenges. Future research directions include developing more robust language models, improving abstractive summarization capabilities, and exploring transfer learning and few-shot learning approaches to adapt summarization models to new domains. Incorporating commonsense reasoning, knowledge graphs, and multimodal information can also enhance summarization performance. Ultimately, the goal is to create human-like summarization systems that can understand and distill information effectively across various contexts and domains.
user
Despite advancements, summarization systems still face challenges in handling complex linguistic structures, maintaining factual consistency, and capturing semantic nuances, especially for diverse data sources. Future research aims to develop more robust language models, improve abstractive summarization, leverage transfer learning, incorporate commonsense reasoning and multimodal information, ultimately working towards human-like summarization capabilities across various contexts.
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: Condense the following piece of history into one or two sentences for me:

Before 1895, the area corresponding to modern-day South Gyeongsang Province was part of Gyeongsang Province, one of the Eight Provinces of Korea during the Joseon dynastic kingdom. In 1895, southern Gyeongsang was replaced by the districts of Jinju in the west and Dongnae (modern-day Busan) in the east. In 1896, they were merged to form South Gyeongsang Province.

The provincial capital was originally at Jinju; it moved in 1925 to Busan.During the Japanese rule of Korea, the province was known as Keishōnan-dō. In 1948, South Gyeongsang Province became part of South Korea. In 1963, Busan separated from South Gyeongsang Province to become a Directly Governed City (Jikhalsi). In 1983, the provincial capital moved from Busan to Changwon.
Response: Modern-day South Gyeongsang Province used to be part of Gyeongsang Province until 1895, with its current provincial capital being Changwon after changing twice. 

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.
