Measuring Information Distortion in Hierarchical Ultra long Novel Reconstruction:The Optimal Expansion Ratio
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Abstract (arXiv)
A two stage novel generation framework (outline -> section outline -> manuscript) is widely used in long novel generation,(e.g., textscDOME, textscPlan&Write, textscLong Writer), but study of such framework in ultra long novel(>1M words) reconstruction is little. Building on recent text compression methods (textscLLMZip, textscLLM2Vec), we conduct an information-theoretic analysis to quantify semantic distortion under different compression-expansion ratios. We examine how outline length affects information preservation. Experiments on ultra-long novels show that the optimal compression-expansion ratio significantly reduces semantic distortion compared to other non-optimal compression-expansion ratio.
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References · 21
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9 more
- 2023GPT-who: An Information Density-based Machine-Generated Text Detectorcited by 40
- 2018DeepZip: Lossless Data Compression using Recurrent Neural Networkscited by 33
- 2024Generating Long-form Story Using Dynamic Hierarchical Outlining with Memory-Enhancementcited by 30
- 2024Language Models can Self-Lengthen to Generate Long Textscited by 24
- 2023Improving Pacing in Long-Form Story Planningcited by 21
- 2024Semantic Similarity Matching for Patent Documents Using Ensemble BERT-related Model and Novel Text Processing Methodcited by 18
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- 2023A Comparison of Document Similarity Algorithmscited by 1
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