Write an overview on 'Long-Form Text Summarization with Transformer Language Models'. Cover the following: 1) Challenges in summarizing lengthy documents, 2) How transformer models can leverage long-range context, 3) Techniques for efficient summarization of long inputs, 4) Evaluation of state-of-the-art models on standard benchmarks, 5) Open research problems and future directions.
Write an overview on 'Long-Form Text Summarization with Transformer Language Models'. Cover the following: 1) Challenges in summarizing lengthy documents, 2) How transformer models can leverage long-range context, 3) Techniques for efficient summarization of long inputs, 4) Evaluation of state-of-the-art models on standard benchmarks, 5) Open research problems and future directions.
user
Summarizing long-form text documents like research papers or books is challenging due to the complexity of capturing key information across lengthy inputs. Transformer language models, with their self-attention mechanisms, are well-suited for this task as they can model long-range dependencies. However, their quadratic complexity limits scalability. Recent methods employ techniques like sparse transformer variants, hierarchical encoding, and retrieval-augmented generation to summarize very long inputs efficiently. Evaluation on benchmarks like ArXiv and PubMed show transformer models achieve state-of-the-art performance. Open challenges include handling inconsistencies, improving factual accuracy, and controlling summary attributes like length and focus. Future work can explore efficient pretraining strategies and incorporation of lightweight commonsense reasoning.
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: Read the article below:

Middle-of-funnel content

At this next stage, your target audience is now aware of your business and the solution you provide, and they’re interested.

They trust you enough to make slightly bigger commitments, like signing up for a webinar and engaging with longer-form content; and they’re interested enough in your offering to read brand-specific material like case studies, testimonials, and newsletter emails.

Their goal is to learn more about the solution you provide—both in general and the one specifically offered by your business.

Your goal is to educate them on your offering and set your business apart from competitors—not just with your features and benefits but with your expertise and knowledge.

Next, write a summary of what it says about Middle-of-funnel content
Response: Middle-of-funnel content includes brand-specific content that educates interested audiences that are already considering an offer.

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.
