LLMEval3 vs 博简智慧专利：怎么选？

关于 LLMEval3

LLMEval-Logic is a Chinese logical reasoning benchmark built through a three-stage audit pipeline: (a) annotators authored items forward from real-world stories rather than templating backward from formulas, (b) a hand-written rubric checklist together with the Z3 SMT solver double-audited every natural-language → first-order-logic translation, and (c) a closed-loop adversarial hardening agent workflow discarded items that turned out to be too easy. The dataset has two paired splits — LLMEval-Logic-Base (single-question PL & FOL items with Z3-verified answers, gold formalisations and atom-level NL→FL rubrics) and LLMEval-Logic-Hard (multi-question / sub-question items covering enumeration / counting / uniqueness / alternative-solution / counterfactual reasoning). Three independent runs of 14 frontier LLMs under thinking / no-thinking configurations show the strongest model reaches only 37.5% Item Accuracy on Hard, leaving substantial headroom for frontier reasoning research. Following the contamination-resistant tradition of LLMEval-Fair, only 80% of the corpus is released publicly; the remaining 20% is held out as a private contamination-resistant test set maintained by Fudan NLP Lab.

LLMEval-Fair addresses robustness and fairness concerns in LLM evaluation through a 30-month longitudinal study. Built on a proprietary bank of 220,000 graduate-level questions across 13 academic disciplines, it dynamically samples unseen test sets for each evaluation run. Its automated pipeline ensures integrity via contamination-resistant data curation, a novel anti-cheating architecture, and a calibrated LLM-as-a-judge process achieving 90% agreement with human experts. A study of nearly 60 leading models reveals performance ceilings and exposes data contamination vulnerabilities undetectable by static benchmarks.

LLMEval-Med is a physician-validated benchmark for evaluating LLMs on real-world clinical tasks. It covers five core medical areas (Medical Knowledge, Language Understanding, Reasoning, Ethics & Safety, Text Generation) with 2,996 questions from real electronic health records and expert-designed clinical scenarios. An automated evaluation pipeline with expert-developed checklists is validated through human-machine agreement analysis. 13 LLMs across specialized, open-source, and closed-source categories are evaluated.

博简智慧专利是一款专注于专利领域的AI聊天工具，集查新检索与撰写功能于一体。它能够通过自然语言对话快速分析专利数据库，精准定位相关技术文献，帮助用户判断发明的新颖性；同时，它支持智能生成专利摘要、权利要求书等文书初稿，并提供格式规范建议，大幅提升撰写效率。这款工具主要面向专利代理人、企业知识产权管理者以及科研人员。在日常工作中，它适合用于专利申请前的查新验证、技术交底书的快速梳理，或是应对紧急的专利文件起草需求，让繁琐的知识产权流程变得更加高效。