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cs.AI2026
CausalWAM: Learning the Causes of Actions in World Action Models
Juntao Cheng, Jinzhou Tang, Fan Feng +2
World action models (WAMs) learn latent variables from observations and use these to both predict the evolution of the scene and to generate actions. The prediction has to be of th…
cs.AI2026
Causal Discovery in the Era of Agents
Yujia Zheng, Vishal Verma, Mantej Gill +3
Recent attempts to combine large language models (LLMs) with causal discovery ask models to infer pairwise directions, propose graph structures, or inject language-model outputs as…