English(EN) MARQ: A Modular, LLM-Agnostic Requirement Quality Assessor Infused with Systems Engineering Knowledge

新的MARQ系统利用SE知识提升LLM需求质量评估

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-28 04:00

研究人员开发了MARQ，一个旨在提高大型语言模型（LLM）需求质量评估的新系统。通过整合专家导出的系统工程知识，MARQ旨在提高LLM评估的准确性和一致性。在NASA数据集上使用Claude Opus-5、GPT-5.6 "Sol"和Gemma-3-12B对MARQ进行测试，显示出显著的改进，特别是对于Claude Opus-5，其F1分数中位数达到了0.80。 AI

影响增强了LLM在需求工程中的能力，可能改善系统开发成果。

排序理由该集群描述了一篇详细介绍新系统及其评估的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

本文如何被排名

Signal score: 15 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 该集群描述了一篇详细介绍新系统及其评估的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: paper, product; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: Breaking (< 6h); Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

完整方法见我们的编辑标准。

报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Jannatul Shefa, Alejandro Salado, Paul Wach, Taylan G. Topcu · 2026-10-28 04:00

MARQ：一个融合了系统工程知识的模块化、LLM不可知需求质量评估器

arXiv:2610.36234v1 Announce Type: new Abstract: Requirements engineering (RE) is foundational to systems engineering (SE), as requirement defects can propagate downstream and adversely affect development outcomes. Although large language models (LLMs) are promising for requiremen…

本文如何被排名

报道来源 [1]

MARQ：一个融合了系统工程知识的模块化、LLM不可知需求质量评估器

相关实体

相关话题