揭示大语言模型产生毒性幻觉的内部机制，通过扰动提示词并追踪神经网络电路路径，为AI安全提供新思路。
arXiv:2605.30913v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in conversational settings where user tone ra…
用大模型分析Twitch各游戏社区聊天毒性差异，揭示不同社区的独特模式。
arXiv:2605.24000v1 Announce Type: new Abstract: Toxicity in online gaming communities remains a persistent challenge, manifesting across genres, platf…
LLM对话生成新防御：剪除有毒子词，提升模型安全性
arXiv:2410.04155v2 Announce Type: replace Abstract: How to defend large language models (LLMs) from generating toxic content is an important research …
一篇对LLM毒性问题进行系统性复制研究的最新论文，验证了现有测量与缓解方法、揭示关键发现，值得关注。
arXiv:2605.14087v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) trained on web-scale corpora inherently absorb toxic patterns f…