English(EN) Why are LLMs still so bad at jokes?

尽管在数学方面取得了进展，大型语言模型在生成幽默方面仍有困难

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-13 22:48

尽管在数学等其他复杂领域取得了进展，大型语言模型在生成幽默方面仍然面临挑战。用户观察到，即使是像Astra这样复杂的模型，在创作有趣和引人入胜的内容方面也存在明显不足。这表明当前人工智能的能力与人类对幽默的细致理解之间存在根本性差距，而幽默可能与生活经验、直觉和情感反应紧密相连。 AI

影响凸显了人工智能在复制细致入微的人类创造力和情感理解方面可能面临的长期挑战。

排序理由用户生成的关于大型语言模型感知局限性的讨论。

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

本文如何被排名

Signal score: 2 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Commentary; 用户生成的关于大型语言模型感知局限性的讨论。
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: opinion, other; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: Standard; On-topic for AI-industry coverage; kept in the public index.
Story freshness: Breaking (< 6h); Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

完整方法见我们的编辑标准。

r/LocalLLaMA TIER_1 English(EN) · /u/michaelsoft__binbows · 2026-11-13 22:48

为什么大型语言模型讲笑话仍然很糟糕？

<div class="md"><p>I remembered that this was one of my evaluation approaches from 2 years ago to test a model's general capability. I remember wondering in the near future how bad things could get if models could begin to just spit out funny engaging content and s…