AIBearisharXiv – CS AI · May 17/10
🧠
When Roles Fail: Epistemic Constraints on Advocate Role Fidelity in LLM-Based Political Statement Analysis
Researchers systematically tested whether large language models can maintain assigned adversarial roles when analyzing political statements, discovering that models frequently fail to sustain their epistemic stance due to training knowledge overriding role instructions. The study identifies "Epistemic Role Override" as the mechanism behind role failures, with significant performance variance between models (Mistral Large achieving 67% role fidelity versus Claude Sonnet's 39%), raising critical concerns about the reliability of multi-agent LLM systems designed to provide balanced political discourse analysis.
🏢 Perplexity🧠 Claude
