LegalWorld is a life-cycle interactive environment modeling Chinese civil litigation as five causally connected stages grounded in 75,309 judgments, paired with LongJud-Bench for cross-stage agent evaluation.
Simulating society requires simulating thought
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CogInstrument represents human reasoning as revisable cognitive motifs in graphical form to support iterative alignment with LLMs during planning tasks, with a N=12 study indicating gains in targeted revision, agency, and trust over standard dialogue interfaces.
An LLM-driven agent-based model with multi-round dialogue reproduces non-linear social influence patterns in vaccination opinion dynamics, with memory increasing resistance and prompt diversity increasing adoption.
Persona prompting in multimodal LLMs for urban sentiment yields high within-persona stability but limited cross-persona variation, with no-persona models often matching or exceeding persona-conditioned agreement to human labels.
citing papers explorer
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LegalWorld: A Life-Cycle Interactive Environment for Legal Agents
LegalWorld is a life-cycle interactive environment modeling Chinese civil litigation as five causally connected stages grounded in 75,309 judgments, paired with LongJud-Bench for cross-stage agent evaluation.
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CogInstrument: Modeling Cognitive Processes for Bidirectional Human-LLM Alignment in Planning Tasks
CogInstrument represents human reasoning as revisable cognitive motifs in graphical form to support iterative alignment with LLMs during planning tasks, with a N=12 study indicating gains in targeted revision, agency, and trust over standard dialogue interfaces.
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A Large Language Model-Driven Agent-Based Modeling Framework with Multi-Round Communication for Simulating Vaccine Opinion Dynamics
An LLM-driven agent-based model with multi-round dialogue reproduces non-linear social influence patterns in vaccination opinion dynamics, with memory increasing resistance and prompt diversity increasing adoption.
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Stable Behavior, Limited Variation: Persona Validity in LLM Agents for Urban Sentiment Perception
Persona prompting in multimodal LLMs for urban sentiment yields high within-persona stability but limited cross-persona variation, with no-persona models often matching or exceeding persona-conditioned agreement to human labels.
- Persona Prompting in Multimodal Urban Perception: Descriptive Convergence and Interpretive Variation