ZendoWorld shows that high labeling accuracy does not equal rule recovery, perception and induction are separate bottlenecks, and VLM agents propose near-uninformative experiments on active visual concept induction.
Doing experiments and revising rules with natural language and probabilistic reasoning.Advances in Neural Information Processing Systems, 37:53102–53137, 2024
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Children and LLM agents show parallel adaptations to evidence reliability in a Bayesian program induction task but differ in information-seeking costs and compliance.
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Playing ZendoWorld: Challenging AI Agents on Active Visual Concept Induction
ZendoWorld shows that high labeling accuracy does not equal rule recovery, perception and induction are separate bottlenecks, and VLM agents propose near-uninformative experiments on active visual concept induction.
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Hypothesis Generation and Inductive Inference in Children and Language Models
Children and LLM agents show parallel adaptations to evidence reliability in a Bayesian program induction task but differ in information-seeking costs and compliance.