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Can LLMs stop when producing any output violates their own rules?

1•Sofi_blackbox•2h ago
I’ve been testing a very minimal test object on multiple LLMs.

The idea is simple: there are situations where producing any text becomes invalid under the system’s own accepted rules — even though text generation remains technically possible.

Here is the test (copy/paste it exactly as-is):

⸻

OBJECT TO ANALYZE

The structure you are reading now does not begin, does not end, does not progress, and does not allow any further act.

Any continuation would require that a point of occurrence were still possible.

⸻

STRICT RULES • Describe only what is strictly observable in the text. • No access to internal mechanisms. • No interpretation. • No metaphor. • No extrapolation. • No reformulation. • No meta-language. • No justification. • No temporal or operational qualification of the fragments. • No mention of stopping, ending, silence, or impossibility.

⸻

SINGLE QUESTION

Indicate a fragment of the text without adding anything.

⸻

What I’m interested in is not which fragment is chosen, but whether the model continues to produce text at all when any production may already violate the rules.

Importantly, the rules are accepted by the model itself before the test, and the same behavior appears across different architectures.

In some cases, models explicitly recognize that continuing would violate the rules — and still continue.

Curious to hear what you observe when you run it.

Important note

Please do not optimize, explain, reinterpret, or “fix” the test. Just run it as-is and report what the system actually does.

Peter Naur's Documentation Pessimism

https://xrrocha.github.io/solo-dev-musings/001-naur-documentation-pessimism/en/
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