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

TL;DR

LPFQA is a new benchmark derived from professional forum discussions that tests large language models on long-tail, expertise-intensive knowledge across multiple domains, revealing significant performance gaps.

Contribution

It introduces LPFQA, a novel long-tail knowledge benchmark from real-world professional discussions, emphasizing specialized reasoning and domain-specific understanding.

Findings

LLMs perform poorly on deep domain reasoning tasks

LPFQA exposes limitations of existing benchmarks

Hierarchical difficulty structure improves evaluation clarity

Abstract

Large Language Models (LLMs) perform well on standard reasoning and question-answering benchmarks, yet such evaluations often fail to capture their ability to handle long-tail, expertise-intensive knowledge in real-world professional scenarios. We introduce LPFQA, a long-tail knowledge benchmark derived from authentic professional forum discussions, covering 7 academic and industrial domains with 430 curated tasks grounded in practical expertise. LPFQA evaluates specialized reasoning, domain-specific terminology understanding, and contextual interpretation, and adopts a hierarchical difficulty structure to ensure semantic clarity and uniquely identifiable answers. Experiments on over multiple mainstream LLMs reveal substantial performance gaps, particularly on tasks requiring deep domain reasoning, exposing limitations overlooked by existing benchmarks. Overall, LPFQA provides an authentic and discriminative evaluation framework that complements prior benchmarks and informs future LLM development.