https://answer.freetools.me/tags/negbench/ Recent content in NegBench on Answer Hugo -- 0.152.2 zh-cn Thu, 12 Mar 2026 20:41:49 +0800 https://answer.freetools.me/%E5%A4%A7%E6%A8%A1%E5%9E%8B%E4%B8%BA%E4%BD%95%E8%AF%BB%E4%B8%8D%E6%87%82%E4%B8%8D%E5%AD%97%E4%BB%8E%E6%B3%A8%E6%84%8F%E5%8A%9B%E6%9C%BA%E5%88%B6%E5%88%B0%E8%AE%AD%E7%BB%83%E6%95%B0%E6%8D%AE%E7%9A%84%E5%90%A6%E5%AE%9A%E8%AF%8D%E5%9B%B0%E5%A2%83/ Thu, 12 Mar 2026 20:41:49 +0800 https://answer.freetools.me/%E5%A4%A7%E6%A8%A1%E5%9E%8B%E4%B8%BA%E4%BD%95%E8%AF%BB%E4%B8%8D%E6%87%82%E4%B8%8D%E5%AD%97%E4%BB%8E%E6%B3%A8%E6%84%8F%E5%8A%9B%E6%9C%BA%E5%88%B6%E5%88%B0%E8%AE%AD%E7%BB%83%E6%95%B0%E6%8D%AE%E7%9A%84%E5%90%A6%E5%AE%9A%E8%AF%8D%E5%9B%B0%E5%A2%83/ 深入解析大语言模型处理否定词的困境：从CondaQA基准测试的42%准确率到视觉语言模型的随机表现，揭示否定词理解失败的技术根源。涵盖否定词的语言学分类、注意力机制的内在缺陷、训练数据分布偏差，以及从自监督预训练到提示词工程的完整解决方案。