CSWAM: Better Causal Semantic Representations for Out-of-Distribution Generalization in World Action Models

A technical paper on improving causal representation learning for world action models, with no direct safety or misuse implications.

Auto-scored: This is a standard machine learning methods paper with no documented risk or mitigation relevance to AI safety.