בחינת עמידה בכללים של נבחרי LLM במשחק CoC TRPG

תקציר מקורי באנגליתarXiv:2607.02802v2 Announce Type: replace Abstract: As LLMs are increasingly deployed as autonomous adjudicators in games such as Call of Cthulhu (CoC), robust rule adherence becomes critical when user intent conflicts with system rules. However, as these models are trained to be helpful and compliant, they may be vulnerable to a class of manipulations we term Rhetorical Injection, where adversarial users exploit narrative framing techniques such as pseudo-logical reasoning and authoritative coercion to bypass adjudication logic. We present CoC-Seduce, a multi-agent adversarial benchmark built on CoC, a Tabletop Role-Playing Game (TRPG) in which rules are explicit about which risky actions require adjudication, yet interaction remains entirely in natural language. Three LLMs, i.e., GPT-5.4