Author

Ao Li

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#machine learning Preprint Sep 2026

FIRM-WM: State-factorized factual-interventional recurrent modeling for reward-free visual planning

FMM-WM (Factual--Interventional Recurrent World Model), a compact pixel world model designed around a typed, goal--comparable configuration from a 128-dimensional dynamic fiber used for prediction but excluded from the terminal goal cost, is introduced.

Yi-Lun Wu, Yun-Jian Zhang, Ao Li et al. · 0 citations

#artificial intelligence Preprint Jun 2026

HyperWorld: Hypergraph-Structured State Serialization Improves Learned Textual World Models

HyperWorld, a controlled study of state serialization for learned textual world models, shows that higher-order state organization is a simple but effective inductive bias for learned symbolic world models, especially when model capacity is limited or test environments differ from training.

Yun-Jian Zhang, Chen-Wei Liang, Tian-Yi Zhang et al. · 0 citations