Technical solutions for intelligent processing of long documents
For long papers or requirement documents that exceed the LLM processing limit, DeepCode employs the following strategies to ensure the quality of processing:
- semantic segmentation algorithmIntelligent segmentation based on document structure (chapters/paragraphs) and content topics to maintain logical coherence
- Academic papers: segmented by Abstract/Methodology/Results
- Requirements Documentation: Segmented by Functional Module
- context-sensitive mechanisms: Establishing cross-passage semantic associations through vector databases ensures that key information is not lost during subsequent integration.
- Abstract chain processing: Each segment is processed to generate a structured summary, which is eventually integrated by the coordinating intelligences to produce a complete understanding.
operation suggestion::
- For documents of more than 50 pages, it is recommended to divide the logical chapters in advance
- Segment status is displayed during system processing, and incorrect segments can be manually corrected.
- Eventually, a segmented processing report will be generated, showing the results of key information extraction for each segment
The solution can stably process technical documents up to 200 pages long with an accuracy improvement of 40% over traditional methods.
This answer comes from the articleDeepCode: an intelligent body system that automatically generates papers and text into codeThe
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