WebNovelBench: Placing LLM Novelists on the Web Novel Distribution

• URL: http://arxiv.org/abs/2505.14818v1
• Date: Tue, 20 May 2025 18:32:28 GMT
• Title: WebNovelBench: Placing LLM Novelists on the Web Novel Distribution
• Authors: Leon Lin, Jun Zheng, Haidong Wang,
• Abstract summary: WebNovelBench is a novel benchmark specifically designed for evaluating long-form novel generation.<n>We leverage a dataset of over 4,000 Chinese web novels, framing evaluation as a synopsis-to-story generation task.<n>Scores are aggregated using Principal Component Analysis and mapped to a percentile rank against human-authored works.
• Score: 4.856346101661866
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Robustly evaluating the long-form storytelling capabilities of Large Language Models (LLMs) remains a significant challenge, as existing benchmarks often lack the necessary scale, diversity, or objective measures. To address this, we introduce WebNovelBench, a novel benchmark specifically designed for evaluating long-form novel generation. WebNovelBench leverages a large-scale dataset of over 4,000 Chinese web novels, framing evaluation as a synopsis-to-story generation task. We propose a multi-faceted framework encompassing eight narrative quality dimensions, assessed automatically via an LLM-as-Judge approach. Scores are aggregated using Principal Component Analysis and mapped to a percentile rank against human-authored works. Our experiments demonstrate that WebNovelBench effectively differentiates between human-written masterpieces, popular web novels, and LLM-generated content. We provide a comprehensive analysis of 24 state-of-the-art LLMs, ranking their storytelling abilities and offering insights for future development. This benchmark provides a scalable, replicable, and data-driven methodology for assessing and advancing LLM-driven narrative generation.

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