LPFQA: A Long-Tail Professional Forum-based Benchmark for LLM Evaluation

• URL: http://arxiv.org/abs/2511.06346v1
• Date: Sun, 09 Nov 2025 12:02:19 GMT
• Title: LPFQA: A Long-Tail Professional Forum-based Benchmark for LLM Evaluation
• Authors: Liya Zhu, Peizhuang Cong, Aowei Ji, Wenya Wu, Jiani Hou, Chunjie Wu, Xiang Gao, Jingkai Liu, Zhou Huan, Xuelei Sun, Yang Yang, Jianpeng Jiao, Liang Hu, Xinjie Chen, Jiashuo Liu, Jingzhe Ding, Tong Yang, Zaiyuan Wang, Ge Zhang, Wenhao Huang,
• Abstract summary: Large Language Models (LLMs) have made rapid progress in reasoning, question answering, and professional applications.<n>Current datasets often focus on simplified tasks or artificial scenarios, overlooking long-tail knowledge and the complexities of real-world applications.<n>We propose LPFQA, a long-tail knowledge-based benchmark derived from authentic professional forums across 20 academic and industrial fields.
• Score: 25.746010737879683
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Large Language Models (LLMs) have made rapid progress in reasoning, question answering, and professional applications; however, their true capabilities remain difficult to evaluate using existing benchmarks. Current datasets often focus on simplified tasks or artificial scenarios, overlooking long-tail knowledge and the complexities of real-world applications. To bridge this gap, we propose LPFQA, a long-tail knowledge-based benchmark derived from authentic professional forums across 20 academic and industrial fields, covering 502 tasks grounded in practical expertise. LPFQA introduces four key innovations: fine-grained evaluation dimensions that target knowledge depth, reasoning, terminology comprehension, and contextual analysis; a hierarchical difficulty structure that ensures semantic clarity and unique answers; authentic professional scenario modeling with realistic user personas; and interdisciplinary knowledge integration across diverse domains. We evaluated 12 mainstream LLMs on LPFQA and observed significant performance disparities, especially in specialized reasoning tasks. LPFQA provides a robust, authentic, and discriminative benchmark for advancing LLM evaluation and guiding future model development.

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