BadWAM: When World-Action Models Dream Right but Act Wrong

World-action models (WAMs) are emerging as a promising foundation for embodied control: rather than predicting actions alone, they learn representations that couple action generation with future world prediction. This coupling is often viewed as a source of robustness, interpretability, and safety, as a robot's action can in principle be checked against its imagined future. In this paper, we show that this assumption is fragile. We introduce BadWAM, a unified framework for modeling and evaluatin

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ethics.ai (16 July 2026), “BadWAM: When World-Action Models Dream Right but Act Wrong,” evidence record 11624, https://ethics.ai/record/11624 (originally published by arXiv cs.LG).

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