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Found 6 papers, 1 papers with code
The Wisdom of Partisan Crowds: Comparing Collective Intelligence in Humans and LLM-based Agents
Human groups are able to converge on more accurate beliefs through deliberation, even in the presence of polarization and partisan bias -- a phenomenon known as the "wisdom of partisan crowds."
Simulating Opinion Dynamics with Networks of LLM-based Agents
Accurately simulating human opinion dynamics is crucial for understanding a variety of societal phenomena, including polarization and the spread of misinformation.
Learning interactions to boost human creativity with bandits and GPT-4
This paper considers how interactions with AI algorithms can boost human creative thought.
Semantic Feature Verification in FLAN-T5
This study evaluates the potential of a large language model for aiding in generation of semantic feature norms - a critical tool for evaluating conceptual structure in cognitive science.
Human-machine cooperation for semantic feature listing
Semantic feature norms, lists of features that concepts do and do not possess, have played a central role in characterizing human conceptual knowledge, but require extensive human labor.
Conceptual structure coheres in human cognition but not in large language models
Neural network models of language have long been used as a tool for developing hypotheses about conceptual representation in the mind and brain.
