Semantic Bayesian World Models

arXiv:2609.03834 · cs.AI, cs.DB, cs.LG · Submitted 2026-09-03 · Read on arXiv

cs.AI, cs.DB, cs.LG

Submitted: 2026-09-03

Updated: 2026-09-03

Comments: 10 pages, under review

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• World Model — 20× in this paper · explained in 7 episodes
• Knowledge Graph — 16× in this paper · explained in 7 episodes
• Knowledge graphs — 13× in this paper · explained in 2 episodes
• Foundation Model — 7× in this paper · explained in 3 episodes
• Foundation Models — 7× in this paper · explained in 7 episodes
• Ontology — 7× in this paper · explained in 2 episodes
• Calibration — 6× in this paper · explained in 7 episodes
• Axioms — 5× in this paper · explained in 2 episodes
• Provenance — 5× in this paper · explained in 3 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Causal Inference — 2× in this paper · explained in 4 episodes
• Grounding — 2× in this paper · explained in 3 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Bayesian Inference — 1× in this paper · explained in 5 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Prompt Engineering — 1× in this paper · explained in 4 episodes
• Sparsity — 1× in this paper · explained in 4 episodes

Sources

• Mastering Diverse Domains through World Models
• Leveraging Log Probabilities in Language Models to Forecast Future Events
• From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought

Related papers

• MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
• Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
• Agents' Last Exam
• The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
• MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
• Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems