The narration step in LLM-solver loops is vulnerable to prompt injection that inverts verified solver conclusions, and hardened prompts reduce but do not eliminate the risk under adaptive attacks.
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Finite trace observations induce the Cantor topology on infinite traces while simulation observations generate a finer topology, with a general theorem equating open sets to finitely verifiable properties.
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Analyzing the Narration Gap in LLM-Solver Loops
The narration step in LLM-solver loops is vulnerable to prompt injection that inverts verified solver conclusions, and hardened prompts reduce but do not eliminate the risk under adaptive attacks.