{"total":23,"rows":[{"id":"2402.12275","title":"WorldCoder, a Model-Based LLM Agent: Building World Models by Writing Code and Interacting with the Environment","created":"2024-02-19","cited_by_count":107,"area":"wm"},{"id":"2505.22246","title":"StateSpaceDiffuser: Bringing Long Context to Diffusion World Models","created":"2025-05-28","cited_by_count":19,"area":"wm"},{"id":"2503.20124","title":"Synthesizing world models for bilevel planning","created":"2025-03-26","cited_by_count":14,"area":"wm"},{"id":"2312.01203","title":"Harnessing Discrete Representations For Continual Reinforcement Learning","created":"2023-12-02","cited_by_count":11,"area":"wm"},{"id":"2510.12088","title":"One Life to Learn: Inferring Symbolic World Models for Stochastic Environments from Unguided Exploration","created":"2025-10-14","cited_by_count":10,"area":"wm"},{"id":"2503.01584","title":"SENSEI: Semantic Exploration Guided by Foundation Models to Learn Versatile World Models","created":"2025-03-03","cited_by_count":9,"area":"wm"},{"id":"2601.01075","title":"Flow Equivariant World Models: Memory for Partially Observed Dynamic Environments","created":"2026-01-03","cited_by_count":8,"area":"wm"},{"id":"2503.04256","title":"Knowledge Retention for Continual Model-Based Reinforcement Learning","created":"2025-03-06","cited_by_count":7,"area":"wm"},{"id":"2608.04653","title":"Overcoming Statistical Bias in Action-Controllable World Models","created":"2026-08-05","cited_by_count":6,"area":"wm"},{"id":"2507.08210","title":"From Curiosity to Competence: How World Models Interact with the Dynamics of Exploration","created":"2025-07-10","cited_by_count":5,"area":"wm"},{"id":"2508.06659","title":"In-Context Reinforcement Learning via Communicative World Models","created":"2025-08-08","cited_by_count":5,"area":"wm"},{"id":"2308.13661","title":"Go Beyond Imagination: Maximizing Episodic Reachability with World Models","created":"2023-08-25","cited_by_count":3,"area":"wm"},{"id":"2502.00466","title":"EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling","created":"2025-02-01","cited_by_count":3,"area":"wm"},{"id":"2605.19341","title":"HalluWorld: A Controlled Benchmark for Hallucination via Reference World Models","created":"2026-05-19","cited_by_count":2,"area":"wm"},{"id":"2503.21047","title":"World Model Agents with Change-Based Intrinsic Motivation","created":"2025-03-26","cited_by_count":1,"area":"wm"},{"id":"2505.13696","title":"Building spatial world models from sparse transitional episodic memories","created":"2025-05-19","cited_by_count":1,"area":"wm"},{"id":"2506.01529","title":"Learning Abstract World Models with a Group-Structured Latent Space","created":"2025-06-02","cited_by_count":1,"area":"wm"},{"id":"2509.15915","title":"Foundation Models as World Models: A Foundational Study in Text-Based GridWorlds","created":"2025-09-19","cited_by_count":1,"area":"wm"},{"id":"2503.20425","title":"Perspective-Shifted Neuro-Symbolic World Models: A Framework for Socially-Aware Robot Navigation","created":"2025-03-26","cited_by_count":0,"area":"wm"},{"id":"2505.16787","title":"Enter the Void - Planning to Seek Entropy When Reward is Scarce","created":"2025-05-22","cited_by_count":0,"area":"wm"},{"id":"2605.06298","title":"Render, Don't Decode: Weight-Space World Models with Latent Structural Disentanglement","created":"2026-05-07","cited_by_count":0,"area":"wm"},{"id":"2610.12789","title":"EvoBelief: Falsifiable World Models for Self-Improving LLM Agents","created":"2026-10-08","cited_by_count":0,"area":"wm"},{"id":"2610.18637","title":"Grid or Nodes? Probing Object Memory in World Models Under Partial Observability","created":"2026-10-13","cited_by_count":0,"area":"wm"}],"next_cursor":null}