Unverified60% confidenceFactExact time
Restricting the model's output options prevents fabrication of new categories, but does not guarantee that the selected category is useful or correct; the so-called zero hallucination merely constrains the output space.
2
Sources
60%
Confidence
Long-term
Relevance
9/18/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedPrompt filtering cannot fundamentally solve the prompt injection problem, because bypass techniques keep emerging and model behavior is non-deterministic; the real line of defense lies in permission boundaries.72% similarUnverifiedJeff-class products restrict output to selecting from a predefined label set, so they will only answer incorrectly with confidence rather than fabricating options from thin air (no hallucination).70% similarUnverifiedReasoning mode can defend against injection only when the model genuinely spends extra tokens redoing the calculation; simply enabling reasoning mode does not guarantee injection protection.69% similarUnverifiedA model actively refusing to answer is semantically completely different from returning empty content; without typed error handling, downstream logic cannot distinguish between the two.69% similarUnverifiedGeneral-purpose large models lack an intrinsic understanding of constraint solver behavior, and the code they generate is often syntactically valid but geometrically over-constrained, under-constrained, or topologically erroneous.69% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/931421API
curl https://kongchang.com/api/v1/knowledge/claims/931421MCP
get_claim(id=931421)