Unverified50% confidenceDecision RuleExact time
LLM nodes are typically used only when parsing pure natural language input or when upstream output is unclear and there are too many downstream branches to handle with if-else; when upstream data is structured, code nodes should be used instead.
1
Sources
50%
Confidence
Long-term
Relevance
9/18/2026
First Seen
Sources
Related Entities
Related Claims
VerifiedThe root cause of prompt injection lies in the fact that LLM architecture encodes system prompts, user inputs, and externally retrieved content uniformly into the same continuous token sequence, making it impossible for the model to distinguish trusted instructions from untrusted data at the semantic level.73% similarUnverifiedLLM 的真正优势在于处理模糊性、非结构化和开放性问题，如自然语言理解与生成、从杂乱文本抽取语义信息72% similarUnverifiedLLMs are architecturally incapable of distinguishing trusted instructions from untrusted input, because they process system instructions and user input as the same text sequence, and a purely technical solution analogous to parameterized queries has yet to emerge.72% similarUnverifiedLLM 在代码任务上的表现往往优于其在纯自然语言推理上的表现，因为代码具有严格语法规则和可验证性71% similarUnverifiedLLMs cannot distinguish instructions from data at a structural level, because both exist in natural language form within the same context window.71% similar
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