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Reasoning Enhances Robustness to Prompt Injection in LLM-Based Consensus
Large Language Models (LLMs) are gaining traction as a method to generate consensus statements and aggregate preferences in digital democracy experiments. Yet, participants can introduce critical vulnerabilities in LLM-based systems. Here, we examine the vulnerability and robustness of off-the-shelf
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