LLMEval3 vs 秘塔AI搜索：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.

秘塔AI搜索是一款无广告、直达结果的AI聊天工具，旨在提供高效、精准的信息检索体验。其核心功能包括智能语义理解，能快速解析用户问题并给出准确答案；结构化结果呈现，将信息以摘要、关键词或关联内容形式清晰展示，省去手动筛选的麻烦；以及多轮对话能力，支持追问和深入探讨，让信息获取更自然流畅。这款工具适合需要快速获取权威信息的研究者、内容创作者、学生及职场人士。使用场景覆盖日常知识查询、学术资料整理、行业趋势分析、写作灵感搜集等，尤其适合对信息时效性和准确性要求较高的用户。