MicroVerse: A Preliminary Exploration Toward a Micro-World Simulation
Recent advances in video generation have opened new avenues for macroscopic simulation of complex dynamic systems, but their application to microscopic phenomena remains largely unexplored. Microscale simulation holds great promise for biomedical applications such as drug discovery, organ-on-chip systems, and disease mechanism studies, while also showing potential in education and interactive visualization. In this work, we introduce MicroWorldBench, a multi-level rubric-based benchmark for microscale simulation tasks. MicroWorldBench enables systematic, rubric-based evaluation through 459 unique expert-annotated criteria spanning multiple microscale simulation task (e.g., organ-level processes, cellular dynamics, and subcellular molecular interactions) and evaluation dimensions (e.g., scientific fidelity, visual quality, instruction following). MicroWorldBench reveals that current SOTA video generation models fail in microscale simulation, showing violations of physical laws, temporal inconsistency, and misalignment with expert criteria. To address these limitations, we construct MicroSim-10K, a high-quality, expert-verified simulation dataset. Leveraging this dataset, we train MicroVerse, a video generation model tailored for microscale simulation. MicroVerse can accurately reproduce complex microscale mechanism. Our work first introduce the concept of Micro-World Simulation and present a proof of concept, paving the way for applications in biology, education, and scientific visualization. Our work demonstrates the potential of educational microscale simulations of biological mechanisms. Our data and code are publicly available at https://github.com/FreedomIntelligence/MicroVerse
69a67822663a122a7ce66844
Rongsheng Wang
claimed_verified
2026-03-03T10:37:24.526Z
63ca949b04c979828315389d
https://cdn-avatars.huggingface.co/v1/production/uploads/63ca949b04c979828315389d/HS5xWNAYjjHeyAAwWJ11l.jpeg
wangrongsheng
wangrongsheng
user
wangrongsheng
69a67822663a122a7ce66845
Minghao Wu
69a67822663a122a7ce66846
Hongru Zhou
69a67822663a122a7ce66847
Zhihan Yu
69a67822663a122a7ce66848
Zhenyang Cai
69a67822663a122a7ce66849
Junying Chen
69a67822663a122a7ce6684a
Benyou Wang
MicroVerse: A Preliminary Exploration Toward a Micro-World Simulation
Recent advances in video generation have opened new avenues for macroscopic simulation of complex dynamic systems, but their application to microscopic phenomena remains largely unexplored. Microscale simulation holds great promise for biomedical applications such as drug discovery, organ-on-chip systems, and disease mechanism studies, while also showing potential in education and interactive visualization. In this work, we introduce MicroWorldBench, a multi-level rubric-based benchmark for microscale simulation tasks. MicroWorldBench enables systematic, rubric-based evaluation through 459 unique expert-annotated criteria spanning multiple microscale simulation task (e.g., organ-level processes, cellular dynamics, and subcellular molecular interactions) and evaluation dimensions (e.g., scientific fidelity, visual quality, instruction following). MicroWorldBench reveals that current SOTA video generation models fail in microscale simulation, showing violations of physical laws, temporal inconsistency, and misalignment with expert criteria. To address these limitations, we construct MicroSim-10K, a high-quality, expert-verified simulation dataset. Leveraging this dataset, we train MicroVerse, a video generation model tailored for microscale simulation. MicroVerse can accurately reproduce complex microscale mechanism. Our work first introduce the concept of Micro-World Simulation and present a proof of concept, paving the way for applications in biology, education, and scientific visualization. Our work demonstrates the potential of educational microscale simulations of biological mechanisms. Our data and code are publicly available at https://github.com/FreedomIntelligence/MicroVerse
Current video generation models struggle with microscale simulation tasks, prompting the development of MicroVerse, a specialized video generation model trained on expert-verified simulation data to accurately reproduce complex microscopic mechanisms.
video generation microscale simulation microscopic phenomena biomedical applications organ-on-chip systems disease mechanism studies educational visualization MicroWorldBench expert-annotated criteria MicroSim-10K MicroVerse