Long-Document Summarization Task

A Long-Document Summarization Task is a entire-document summarization task that involves long documents.

• Context:
  • It can (typically) involve processing variable-scale documents, where the size and complexity of the document pose challenges to traditional summarization algorithms due to computational or context retention constraints.
  • It can (typically) require handling of various data formats, including but not limited to PDF files, digital books, and long web articles, necessitating flexible preprocessing and normalization steps.
  • It can be supported by a Long-Document Summarization System (that implements a long-document summarization task).
  • ...
• Example(s):
  • Full-Length Book Synopsis Generation.
  • Lengthy Scientific Article Abstract Generation.
  • Lengthy Contract Summarization, for lengthy contracts.
  • ...
• Counter-Example(s):
  • Short Document Summarization Task, such as: short news article summarization or blog post summarization.
  • Long-Document Keyword Extraction (keyword extraction).
  • Large-Image Caption Generation.
  • Real-time transcription summarization of meetings, which typically involves shorter, more immediate content.
• See: Automatic Summarization, Text Simplification.Chunking Strategy, MapReduce Summarization Technique, Iterative Refinement, Natural Language Processing (NLP), Large Language Models (LLMs), Text Summarization Task, Variable-Scale Documents.

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References

2023

• (Chakraborty, 2023) ⇒ Anirban Chakraborty. (2023). “Challenges of LLM for Large Document Summarization: Exploring different LangChain approaches using Google Cloud Vertex AI PaLM2 API." In: Google Cloud - Community.
  • QUOTE: "Although summarizing a short paragraph is a trivial task, summarizing large documents such as a PDF file with multiple pages can be challenging... We will go through a few examples of how we can use generative models along with LangChain strategies to summarize large documents."

2022

• (Cho et al., 2022) ⇒ Sangwoo Cho, Kaiqiang Song, Xiaoyang Wang, Fei Liu, and Dong Yu. (2022). “Toward Unifying Text Segmentation and Long Document Summarization.” doi:10.48550/arXiv.2210.16422
  • NOTE: It addresses the challenge of summarizing long documents, such as scientific papers and spoken transcripts, which are complex due to their length and detailed structure.

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