Robots discover causal tool features through VLM suggestions and physics-based counterfactual perturbations in simulation, then transfer manipulation skills via conditioned keypoint matching.
Cambridge University Press, 2 edition
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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BGM-IV performs nonlinear IV regression by inferring causally structured latent components and replacing the outcome likelihood with an instrument-averaged pseudo-likelihood, showing strongest results in high-dimensional covariate regimes.
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Creative Robot Tool Use by Counterfactual Reasoning
Robots discover causal tool features through VLM suggestions and physics-based counterfactual perturbations in simulation, then transfer manipulation skills via conditioned keypoint matching.
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BGM-IV: an AI-powered Bayesian generative modeling approach for instrumental variable analysis
BGM-IV performs nonlinear IV regression by inferring causally structured latent components and replacing the outcome likelihood with an instrument-averaged pseudo-likelihood, showing strongest results in high-dimensional covariate regimes.