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Found 6 papers, 3 papers with code
Probing BERT’s priors with serial reproduction chains
Sampling is a promising bottom-up method for exposing what generative models have learned about language, but it remains unclear how to generate representative samples from popular masked language models (MLMs) like BERT.
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.
Mixed-effects transformers for hierarchical adaptation
Language use differs dramatically from context to context.
Open-domain clarification question generation without question examples
An overarching goal of natural language processing is to enable machines to communicate seamlessly with humans.
Pragmatic inference and visual abstraction enable contextual flexibility during visual communication
On each trial, both participants were shown the same four objects, but in different locations.
