PERSUASIONTRACE introduces a Bayesian-network simulated target for multi-turn persuasion that matches human belief dynamics (81 vs 80) better than LLM baselines (64) and enables process-level evaluation.
Measuring and Benchmarking Large Language Models' Capabilities to Generate Persuasive Language
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Presents HarmAmp benchmark for multi-turn harm amplification in LLMs and TrajSafe proactive monitor that reduces harm while keeping low over-refusal and preserving capabilities.
Literature on system prompts for AI shows fragmented and contradictory claims that complicate policy efforts to use them as reliable governance mechanisms.
citing papers explorer
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A Model of Multi-turn Human Persuadability Using Probabilistic Belief Tracing
PERSUASIONTRACE introduces a Bayesian-network simulated target for multi-turn persuasion that matches human belief dynamics (81 vs 80) better than LLM baselines (64) and enables process-level evaluation.
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Investigating and Alleviating Harm Amplification in LLM Interactions
Presents HarmAmp benchmark for multi-turn harm amplification in LLMs and TrajSafe proactive monitor that reduces harm while keeping low over-refusal and preserving capabilities.