LLM World Models

LLM: Large Language Model

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2 papers in the last four weeks, with none the four weeks before. 0.0% of all new papers.

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From Traces to Agentic Worlds: Agentic Language World Models for Interactive Environment Simulation
Oct 5, 2026Quanyu Long, Xiao Chen, Jianda Chen +4LLM World Models Interactive World Models
Nanyang Technological University · The Hong Kong Polytechnic University
Do World Models Learn Global Understanding?
Sep 28, 2026Alexander Detkov, Matt ThomsonLLM World Models World Model Learning
California Institute of Technology Pasadena, CA 91125, USA
Agent-Editing World Model: Rethinking World Modeling for LLM Agents
Sep 23, 2026Shuang Sun, Guoxin Chen, Fanzhe Meng +6LLM World Models World Models
Gaoling School of Artificial Intelligence, Renmin University of China
MemWM: Memory-Augmented Text-Based World Model
Aug 7, 2026Yujun Wang, Tao Zhang, Jinhe Bi +9LLM World Models World Model Learning
LMU Munich · Munich Center for Machine Learning (MCML) · Huawei Heisenberg Research Center +4
Transformers Struggle to Use Their Emergent World Models: Revisiting the Tower of Hanoi, and the Illusion of Thinking
Aug 7, 2026Devin Pereira, Willem ZuidemaLLM World Models LLM Planning
1Artificial Intelligence Program, University of Amsterdam · ELLIS Unit Amsterdam · Institute for Logic Language and Computation, University of Amsterdam
EnvACE: Internalizing Environment Dynamics via World Rehearsal for Agentic Reinforcement Learning
Aug 6, 2026Zishan Xu, Zhiyuan Yao, Yuxin Chen +9LLM World Models Agentic RL
Shanghai Jiao Tong University · Zhejiang University · National University of Singapore +4
DreamGuard: Efficient Runtime Guardrail for LLM Agents via Risk-Aware World Model
Aug 6, 2026Wenhao Lin, Chenyu Yu, Xingwei Lin +6LLM World Models LLM Guardrails
Zhejiang University · Nanjing University of Posts and Telecommunications · Sun Yat-sen University
Simulate to Generalize: Scaling Stateful Supervision for API-calling Agents using LLM World Models
Jul 18, 2026Seanie Lee, Sanjoy Chowdhury, Chao Jiang +5LLM World Models Synthetic Data Generation
Apple
When a Verified World Model Still Loses: Play-Adequacy vs Prediction-Accuracy in LLM-Synthesized Code World Models
Jul 15, 2026Javier Aguilar MartínLLM World Models World Models
AGILabs (javieraguilar.ai)
From Tokens to States: LLMs as a Special Case of World Models and the Continuous Path Beyond
Jun 26, 2026Paul DuboisLLM World Models World Models
Qwen-AgentWorld: Language World Models for General Agents
Jun 23, 2026Yuxin Zuo, Zikai Xiao, Li Sheng +30LLM World Models Agentic RL
Qwen Team
NarrativeWorldBench: A Frontier-Saturated Benchmark and a Latent World Model for Long-Horizon Co-Creative Audio Drama
Jun 16, 2026Logan Mann, Abdur Rahman, Mohammad Saifullah +2LLM World Models Multilingual Language Model Evaluation
University of California, Santa Barbara · Pocket FM
Bridging the Agent-World Gap: Text World Models for LLM-based Agents
Jun 8, 2026Yixia Li, Hongru Wang, Peng Lai +13LLM World Models World Models
Southern University of Science and Technology · University of Edinburgh · Peking University +5
CoMAP: Co-Evolving World Models and Agent Policies for LLM Agents
Jun 1, 2026Youwei Liu, Jian Wang, Hanlin Wang +1LLM World Models LLM Agent Training
Central South University · College of Computer Science, Sichuan University · Department of Computing, The Hong Kong Polytechnic University
Do LLMs Build World Models From Text? A Multilingual Diagnostic of Spatial Reasoning
May 27, 2026Zhikai Pan, Chih-Ting Liao, Chunrui Liu +5LLM World Models Multilingual Language Model Evaluation
University of New South Wales · Essential Energy · University of Alabama at Birmingham +3
MCP-Cosmos: World Model-Augmented Agents for Complex Task Execution in MCP Environments
May 9, 2026Giridhar Ganapavarapu, Dhaval PatelLLM World Models World Models
IBM, New York
World Properties without World Models: Distributional Associations and the Interpretation of Decoding Results from Language Models
Mar 4, 2026Elan BarenholtzLLM World Models Word Embeddings
Department of Psychology & Center for Complex Systems and Brain Sciences Florida Atlantic University
Neuro-Symbolic Synergy for World Modeling
Feb 11, 2026Hongyu Zhao, Siyu Zhou, Haolin Yang +2LLM World Models World Model Learning
Department of Computer Science University of Maryland College Park, MD 20742, USA · Faculty of Engineering and IT Australian AI Institute University of Technology Sydney Sydney, Australia · Department of Statistics University of Chicago Chicago, IL 60637, USA +2

Oct 5, 2026, cs.CLJ/K move · Enter open · S save

From Traces to Agentic Worlds: Agentic Language World Models for Interactive Environment Simulation

Quanyu Long, Xiao Chen, Jianda Chen, Haozhen Zhang+3

Nanyang Technological University · The Hong Kong Polytechnic University

LLM World Models Interactive World Models

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Realistic environment replicas are increasingly valuable for training and evaluating LLM agents, yet the original systems may be inaccessible or impractical to reproduce. We explore agentic language world modeling: rather than rebuilding an executable environment, a world model agent serves as the environment for a task agent and supports faithful and stateful simulation. We instantiate this paradigm with Trace2Env, a learning-free framework for settings where the original system is unavailable but historical interaction traces remain accessible. Trace2Env reconstructs these traces into a reusable environment worldbook containing environment schemas, grounded evidence, and induced behavioral knowledge. At runtime, the world model agent actively consults the worldbook together with persistent episodic state to infer each action's observation and lasting state effects. Across nine environments, Trace2Env improves both next-observation fidelity and long-horizon interaction consistency over conventional prompt-based LWMs. In multi-turn interaction, task agent actions generated against Trace2Env remain valid more often when replayed in the real environment, indicating that its simulated dynamics better preserve the consequences of earlier actions across successive turns. These results establish agentic language world modeling as an alternative direction for building realistic environment replicas without reconstructing the original executable system.

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