Unverified50% confidenceFactExact time
Custom instructions correspond at the underlying level to the system prompt mechanism of large language models; system prompts have the highest priority and are not visible to users.
1
Sources
50%
Confidence
Long-term
Relevance
9/22/2026
First Seen
Sources
Related Entities
Related Claims
Unverified在大语言模型底层，系统提示词、用户输入和模型输出都是同一个token序列的不同片段，依靠特殊分隔符和训练时植入的行为模式维持边界，而非硬件或操作系统级别的隔离77% similarUnverifiedTONGYI Lingma's underlying layer relies on the code understanding and generation capabilities of the Tongyi Qianwen series of large language models.76% similarUnverifiedThe context and constraints provided by the user directly determine the direction and quality of the large language model's generation, which is why prompt engineering is important.75% similarUnverifiedLLM-based dialogue systems handle open-ended input through deep semantic understanding and can infer user intent without explicit keywords75% similarVerifiedThe 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.74% similar
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