研究人员开发了NCO，这是一种旨在增强对大型语言模型（LLM）输出控制的新解码策略。该插件解决了防止多种禁止模式（如脏话或个人身份信息（PII））出现在生成文本中的挑战。NCO通过执行高效的在线模式匹配来实现这一点，避免了将多个约束转换为单个自动机时常见的状态爆炸问题。该策略与标准推理方法兼容，并在实际应用中证明了其有效性。 AI
影响 为LLM提供了一种更有效的方法来避免生成有害或敏感内容。
排序理由 该集群描述了一篇关于LLM新型解码策略的学术论文。
AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →
完整方法见我们的编辑标准。
Controlling Large Language Models (LLMs) to prevent the generation of undesirable content, such as profanity and personally identifiable information (PII), has become increasingly critical. While earlier approaches relied on post-processing or resampling, recent research has shif…
Controlling Large Language Models (LLMs) to prevent the generation of undesirable content, such as profanity and personally identifiable information (PII), has become increasingly critical. While earlier approaches relied on post-processing or resampling, recent research has shif…