{"total":23,"rows":[{"id":"2405.17398","title":"Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability","created":"2024-05-27","cited_by_count":347,"area":"wm"},{"id":"2411.14499","title":"Understanding World or Predicting Future? A Comprehensive Survey of World Models","created":"2024-11-21","cited_by_count":166,"area":"wm"},{"id":"2402.10877","title":"Robust agents learn causal world models","created":"2024-02-16","cited_by_count":81,"area":"wm"},{"id":"2507.06952","title":"What Has a Foundation Model Found? Using Inductive Bias to Probe for World Models","created":"2025-07-09","cited_by_count":47,"area":"wm"},{"id":"2406.19501","title":"Monitoring Latent World States in Language Models with Propositional Probes","created":"2024-06-27","cited_by_count":43,"area":"wm"},{"id":"2511.05963","title":"Next-Latent Prediction Transformers Learn Compact World Models","created":"2025-11-08","cited_by_count":31,"area":"wm"},{"id":"2506.01622","title":"General agents contain world models","created":"2025-06-02","cited_by_count":17,"area":"wm"},{"id":"2501.00226","title":"Generative Emergent Communication: Large Language Model is a Collective World Model","created":"2024-12-31","cited_by_count":15,"area":"wm"},{"id":"2502.09297","title":"When Do Neural Networks Learn World Models?","created":"2025-02-13","cited_by_count":8,"area":"wm"},{"id":"2507.21513","title":"What Does it Mean for a Neural Network to Learn a \"World Model\"?","created":"2025-07-29","cited_by_count":8,"area":"wm"},{"id":"2602.06923","title":"From Kepler to Newton: Inductive Biases Guide Learned World Models in Transformers","created":"2026-02-06","cited_by_count":7,"area":"wm"},{"id":"2506.02996","title":"Linear Spatial World Models Emerge in Large Language Models","created":"2025-06-03","cited_by_count":6,"area":"wm"},{"id":"2512.03400","title":"Better World Models Can Lead to Better Post-Training Performance","created":"2025-12-03","cited_by_count":4,"area":"wm"},{"id":"2602.23164","title":"MetaOthello: A Controlled Study of Multiple World Models in Transformers","created":"2026-02-26","cited_by_count":4,"area":"wm"},{"id":"2312.05361","title":"Emergence and Function of Abstract Representations in Self-Supervised Transformers","created":"2023-12-08","cited_by_count":3,"area":"wm"},{"id":"2504.04608","title":"AI in a vat: Fundamental limits of efficient world modelling for agent sandboxing and interpretability","created":"2025-04-06","cited_by_count":3,"area":"wm"},{"id":"2406.00765","title":"The Embodied World Model Based on LLM with Visual Information and Prediction-Oriented Prompts","created":"2024-06-02","cited_by_count":1,"area":"wm"},{"id":"2603.16689","title":"Predictive Statistics Shape Emergent World Representations of Grid Walkers","created":"2026-03-17","cited_by_count":1,"area":"wm"},{"id":"2511.13021","title":"PragWorld: A Benchmark Evaluating LLMs' Local World Model under Minimal Linguistic Alterations and Conversational Dynamics","created":"2025-11-17","cited_by_count":0,"area":"wm"},{"id":"2603.04317","title":"World Properties without World Models: Recovering Spatial and Temporal Structure from Co-occurrence Statistics in Static Word Embeddings","created":"2026-03-04","cited_by_count":0,"area":"wm"},{"id":"2606.03685","title":"A Close Look At World Model Recovery In Supervised Fine-Tuned LLM Planners","created":"2026-06-02","cited_by_count":0,"area":"wm"},{"id":"2606.28127","title":"From Tokens to States: LLMs as a Special Case of World Models and the Continuous Path Beyond","created":"2026-06-26","cited_by_count":0,"area":"wm"},{"id":"2607.24425","title":"Context Is King: How In-Context Specification Shapes the Geometry of Concepts","created":"2026-07-27","cited_by_count":0,"area":"wm"}],"next_cursor":null}