Hugging Face Trending Papers

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents

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Large language models (LLMs) increasingly support complex professional tasks, yet their capabilities in rule-intensive document review remain insufficiently evaluated. National standard documents, such as China GB/T standards, offer a representative testbed: they are lengthy, highly structured, and governed by explicit rules for scope, terminology, normative wording, and cross-section consistency.

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arXiv AI
Jul 14

Automated Textbook Auditing with Multi-Agent LLM Systems

arXiv:2607. 11276v1 Announce Type: cross Abstract: Ensuring the quality of educational materials requires more than standard proofreading: textbooks must be audited for factual accuracy, domain-specific technical correctness, and linguistic quality simultaneously -- a task that general-purpose grammar checkers cannot address.

By Ciprian Cristescu, Adrian-Marius Dumitran, Angela-Liliana Dumitran, Gabriel Stefan
arXiv Computation and Language
Aug 31

Benchmarking LLM-as-a-Judge for Long-Form Output Evaluation

The paper introduces LongJudgeBench, a benchmark designed to evaluate large language models (LLMs) acting as judges for long-form text generation. It highlights that long-form evaluation requires complex, document-level assessments beyond simple length, such as organization, coverage, depth, consistency, and scenario-specific quality. Experiments show a significant reliability gap among current LLM judges, indicating instability across scenarios and limited effectiveness of rubrics or references.

By Junjie Chen, Yuxi Dong, Haitao Li, Weihang Su, Yujia Zhou, Min Zhang, Yiqun Liu, Qingyao Ai