paper

Revising Context, Shifting Simulated Stance: Auditing LLM-Based Stance Simulation in Online Discussions

paperactiveprovisionalrevising-context-shifting-simulated-stance-auditing-llm-based-stance-simulation-in-online-discussions-b7d6365b·1 events·first seen 12d ago

Aliases: Revising Context, Shifting Simulated Stance: Auditing LLM-Based Stance Simulation in Online Discussions

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5arXiv · cs.CL·12d ago·source ↗

Counterfactual context revision framework for auditing LLM-based stance simulation in online discussions

Researchers introduce a counterfactual context revision framework to audit how LLMs simulate individual users' stances in online discussions. By applying controlled text-only and multimodal (meme-based) revisions to conversational contexts, they measure how readily simulated stances shift in response to semantically independent changes. Results show effective and robust stance transitions across both revision types and polarization-preference mechanisms, raising concerns about whether LLM simulations reflect genuine user-specific beliefs or are highly context-sensitive artifacts. The work contributes an evaluation framework and highlights risks of using LLMs to model online opinion dynamics.

Evaluation and Benchmarking AI Safety Research Revising Context, Shifting Simulated Stance: Auditing LLM-Based Stance Simulation in Online Discussions