3 papers
cs.CL2026
An Industrial-Scale Insurance LLM Achieving Verifiable Domain Mastery and Hallucination Control without Competence Trade-offs
Qian Zhu, Xinnan Guo, Jingjing Huo +5
Adapting Large Language Models (LLMs) to high-stakes vertical domains like insurance presents a significant challenge: scenarios demand strict adherence to complex regulations and…
cs.AI2026
RubricEval: A Rubric-Level Meta-Evaluation Benchmark for LLM Judges in Instruction Following
Tianjun Pan, Xuan Lin, Wenyan Yang +7
Rubric-based evaluation has become a prevailing paradigm for evaluating instruction following in large language models (LLMs). Despite its widespread use, the reliability of these…
cs.CL2025
INSEva: A Comprehensive Chinese Benchmark for Large Language Models in Insurance
Shisong Chen, Qian Zhu, Wenyan Yang +15
Insurance, as a critical component of the global financial system, demands high standards of accuracy and reliability in AI applications. While existing benchmarks evaluate AI capa…