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HyperWorld: Hypergraph-Structured State Serialization Improves Learned Textual World Models
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serializationworld modelshypergraphssymbolic reasoning
2609.00002
Builder Relevance
1h ago80%
Abstract
HyperWorld presents a study on the impact of serialization structure on learned textual world models, demonstrating that hyperedge serialization significantly enhances model performance.
Reality Card
Core Claim
Hyperedge serialization provides the clearest performance gains for learned textual world models, particularly under distribution shift and with limited model capacity.
Method / Result
Hyperedge serialization achieved the highest success rate in downstream greedy planning among tested representations.
Limitations
The study may have limitations in reproducibility due to the specific model scales and data budgets used in the experiments.
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