打破AI公平性评测的“应试教育”，用真实行为模式替代标准化测试分数。
arXiv:2605.12530v2 Announce Type: replace-cross Abstract: LLM fairness should be evaluated through in-situ behavioral pattern rather than standardized…
LLM agent 行为测试新工具，验证做了什么而非说了什么，开源且实用
Article URL: https://github.com/Kareem-Rashed/rubric-eval Comments URL: https://news.ycombinator.com/item?id=48509073 Points: 1 # Comments: 0
从表示层揭示AI安全评估的盲点，为模型对齐提供全新视角与洞见
arXiv:2606.08044v1 Announce Type: new Abstract: Large Language Model (LLM) safety has often been evaluated at the behavior level, which provides limit…
人类心理问卷真的能测准大模型行为？这项研究用八个开源模型揭开了方法论缺陷。
arXiv:2509.10078v4 Announce Type: replace-cross Abstract: We examine whether human psychometric questionnaires can serve as reliable tools for charact…
首个专门评估LLM辅助同行评审行为的基准，揭示AI评审的可靠性边界。
arXiv:2605.29815v1 Announce Type: new Abstract: The growing number of submitted papers has motivated the exploration of Large Language Models (LLMs) a…
开源项目LLM INQUISITOR提供真实场景下的LLM行为评估框架，专注长任务和实用性，而非基准测试。
Article URL: https://github.com/AssimilatedHuman/LLM-Inquisitor Comments URL: https://news.ycombinator.com/item?id=48207330 Points: 1 # Comments: 0