---
title: "Who cites Learning Interactive Real-World — 42 citing papers"
description: "42 papers of the Elamur Research library cite «Learning Interactive Real-World Simulators», found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/papers/yang-2023-learning-interactive-real-world-simulators/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/yang-2023-learning-interactive-real-world-simulators/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Learning Interactive Real-World Simulators](https://md.research.elamur.ai/free/en/papers/yang-2023-learning-interactive-real-world-simulators/) / cited by

# Who cites «Learning Interactive Real-World Simulators»

42 papers of our library cite it (of the 149,439 whose bibliographies we read) · 7 with a page here, the most cited first · [← back to «Learning Interactive Real-World Simulators»](https://md.research.elamur.ai/free/en/papers/yang-2023-learning-interactive-real-world-simulators/)

1. **[Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion](https://md.research.elamur.ai/free/en/papers/huang-2025-self-forcing-bridging-train-test/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xun Huang, Zhengqi Li, Guande He, et al.*2025 · 146 citations*
2. [**Diffusion Models Are Real-Time Game Engines arXiv:2408.14837**Dani Valevski, Yaniv Leviathan, Moab Arar, et al.*2024 · 49 citations*](https://md.research.elamur.ai/free/en/papers/valevski-2024-diffusion-models-real-time-game/)
3. [**Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning arXiv:2312.05230**Zhiting Hu, Tianmin Shu*2023 · 18 citations*](https://md.research.elamur.ai/free/en/papers/hu-2023-language-models-agent-models-world/)
4. [**Generating Code World Models with Large Language Models Guided by Monte Carlo Tree Search arXiv:2405.15383**Nicola Dainese, Matteo Merler, Minttu Alakuijala, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/dainese-2024-generating-code-world-models/)
5. **[Growing Through Experience: Scaling Episodic Grounding in Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-growing-through-experience-scaling-episodic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chunhui Zhang, Sirui Wang, Zhongyu Ouyang, et al.*2025 · 5 citations*
6. **[Can VLMs Predict Future States? Bootstrapping World Models from Inverse Dynamics](https://md.research.elamur.ai/free/en/papers/qiu-2026-can-vlms-predict-future-states/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yifu Qiu, Yftah Ziser, Anna Korhonen, et al.*2026*
7. [**Qwen-AgentWorld: Language World Models for General Agents arXiv:2606.24597**Yuxin Zuo, Zikai Xiao, Li Sheng, et al.*2026*](https://md.research.elamur.ai/free/en/papers/zuo-2026-qwen-agentworld-language-world/)

35 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/yang-2023-learning-interactive-real-world-simulators/) — Learning Interactive Real-World Simulators