Summarize the key points about the evaluation of text summarization systems from the following passage:

Evaluating the quality and performance of text summarization systems is a crucial yet challenging task. Traditionally, evaluation has relied on metrics such as ROUGE, which measure the overlap between system-generated summaries and human-written reference summaries. While ROUGE scores provide a quantitative measure, they have limitations and do not fully capture the nuances of summarization quality, such as coherence, relevance, and factual accuracy. As a result, human evaluation remains an important component, where human annotators manually assess the summaries based on various criteria. However, human evaluation is time-consuming, subjective, and costly, making it difficult to scale. Recent research has explored alternative evaluation methods, such as question-answering based metrics that assess how well summaries can answer questions about the source text. There has also been work on developing reference-free evaluation metrics that do not require human-written summaries, instead relying on principles of language modeling and learned representations. Ultimately, evaluation remains an open challenge, and developing robust, reliable, and scalable evaluation methods is crucial for advancing summarization technology and enabling real-world deployment.
Summarize the key points about the evaluation of text summarization systems from the following passage:

Evaluating the quality and performance of text summarization systems is a crucial yet challenging task. Traditionally, evaluation has relied on metrics such as ROUGE, which measure the overlap between system-generated summaries and human-written reference summaries. While ROUGE scores provide a quantitative measure, they have limitations and do not fully capture the nuances of summarization quality, such as coherence, relevance, and factual accuracy. As a result, human evaluation remains an important component, where human annotators manually assess the summaries based on various criteria. However, human evaluation is time-consuming, subjective, and costly, making it difficult to scale. Recent research has explored alternative evaluation methods, such as question-answering based metrics that assess how well summaries can answer questions about the source text. There has also been work on developing reference-free evaluation metrics that do not require human-written summaries, instead relying on principles of language modeling and learned representations. Ultimately, evaluation remains an open challenge, and developing robust, reliable, and scalable evaluation methods is crucial for advancing summarization technology and enabling real-world deployment.
user
Evaluating text summarization systems is challenging. Traditional metrics like ROUGE measure overlap with reference summaries but have limitations. Human evaluation is important but subjective and costly. Recent research explores alternative methods like question-answering based metrics and reference-free metrics using language modeling. Developing robust, reliable, and scalable evaluation methods remains an open challenge for advancing summarization technology and enabling real-world deployment.
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: Please summarize how Asian American and Pacific Islander Heritage Month was started based on the text below: 

History
A former congressional staffer in the 1970s, Jeanie Jew, first approached Representative Frank Horton with the idea of designating a month to recognize Asian Pacific Americans, following the bicentennial celebrations.[19] In June 1977, Representatives Horton, and Norman Y. Mineta, introduced a United States House of Representatives resolution to proclaim the first ten days of May as Asian-Pacific Heritage Week.[20][21] A similar bill was introduced in the Senate a month later by Daniel Inouye and Spark Matsunaga.[20][22]

The proposed resolutions sought that May be designated for two reasons. For on May 7, 1843, the first Japanese immigrant arrived in the United States.[23][24][25] More than two decades later, on May 10, 1869, the golden spike was driven into the first transcontinental railroad, which was completed using Chinese labor.[23][24][26]

President Jimmy Carter signed a joint resolution for the celebration on October 5, 1978.[20]

On May 1, 2009, President Barack Obama signed Proclamation 8369, recognizing the month of May as Asian American and Pacific Islander Heritage Month.[1][27]
Response: A former congressional staffer with the idea approached a representative about it in the 1970s. In 1977, a resolution was introduced in the House and the Senate, and the President signed it in 1978. However, that resolution was only for the first ten days of May. It wasn't until 2009 that the whole month of May was named Asian American and Pacific Islander Heritage Month.

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.
