SCOPE adds per-pixel action conditioning to pretrained video diffusion models and releases the CrossFPS multi-game dataset to support cross-game FPS world model simulation with zero-shot transfer.
Understanding world or predicting future? a comprehensive survey of world models.ACM Computing Surveys, 58(3):1–38
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MolWorld expands a molecule-transfer graph using a world model to discover high-property molecules that maintain strong structural connectivity to known compounds for actionable optimization.
PhyWorld improves temporal consistency and physical plausibility in video world models via flow matching fine-tuning followed by DPO on physics preference pairs, with reported gains on VBench and a custom physical-faithfulness benchmark.
WorldArena 2.0 extends embodied world model benchmarks to visuotactile perception, interactive policy training, and diverse real and simulated robotic platforms under a unified protocol.
HaM-World integrates soft-Hamiltonian dynamics with selective state-space memory to reduce long-horizon rollout error by 55% and achieve top returns under 12 OOD perturbations on DeepMind Control Suite tasks.
citing papers explorer
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SCOPE: Simulating Cross-game Operations in Playable Environments for FPS World Models
SCOPE adds per-pixel action conditioning to pretrained video diffusion models and releases the CrossFPS multi-game dataset to support cross-game FPS world model simulation with zero-shot transfer.
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MolWorld: Molecule World Models for Actionable Molecular Optimization
MolWorld expands a molecule-transfer graph using a world model to discover high-property molecules that maintain strong structural connectivity to known compounds for actionable optimization.
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PhyWorld: Physics-Faithful World Model for Video Generation
PhyWorld improves temporal consistency and physical plausibility in video world models via flow matching fine-tuning followed by DPO on physics preference pairs, with reported gains on VBench and a custom physical-faithfulness benchmark.
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WorldArena 2.0: Extending Embodied World Model Benchmarking on Modality, Functionality and Platform
WorldArena 2.0 extends embodied world model benchmarks to visuotactile perception, interactive policy training, and diverse real and simulated robotic platforms under a unified protocol.
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HaM-World: Soft-Hamiltonian World Models with Selective Memory for Planning
HaM-World integrates soft-Hamiltonian dynamics with selective state-space memory to reduce long-horizon rollout error by 55% and achieve top returns under 12 OOD perturbations on DeepMind Control Suite tasks.