PhysEditWorld is a new dataset of over 60 million frames from 12 UE5 cinematic scenes with synchronized multimodal signals and explicit gravity labels, built via replay to support physics-editable world models.
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Yume: An interactive world generation model
27 Pith papers cite this work. Polarity classification is still indexing.
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EgoCS-400K is a new 400K-video egocentric CS dataset with action-state-event alignment from public match demos for world model training.
SPAWN enables training-free insertion of custom visual concepts into autoregressive world models by swapping the pinned context-memory anchor over a short injection window.
MBench is a new benchmark that quantifies long-term memory in video world models via three hierarchical consistency dimensions evaluated on curated real videos.
WBench is a benchmark with 289 test cases and 1,058 turns for evaluating interactive world models using 22 automated metrics validated against human judgments.
PREX decomposes target 4D video volumes into Preserve, Reveal, and Expand roles with a region-aware adapter on a frozen diffusion backbone, trained via proxy tasks, and introduces the PREBench benchmark to reduce region-structured editing failures.
WorldMark is the first public benchmark that standardizes scenes, trajectories, and control interfaces across heterogeneous interactive image-to-video world models.
MultiWorld is a scalable framework for multi-agent multi-view video world models that improves controllability and consistency over single-agent baselines in game and robot tasks.
RoboWorld introduces an automated pipeline using autoregressive video world models and task-progress VLM scoring, plus Step Forcing for long-horizon stability, to achieve high correlation with real robot policy evaluation.
PermaVid disentangles spatial context into semantic appearance and geometric structure via multi-modal memory banks and edit-aware updates to maintain long-term consistency in video generation after edits.
MoVerse generates real-time interactive video world models from single narrow-FOV images via panoramic diffusion expansion, Gaussian scaffold lifting, and distillation of a bidirectional diffusion teacher into a causal autoregressive renderer.
A controlled study finds that block-wise state-space recurrence outperforms other memory designs for open-domain scene return in action-conditioned video models, and that standard replay metrics do not adequately measure memory quality.
Prisma-World is a diffusion-based multi-agent video model that uses joint full-attention, multi-agent RoPE, and relative camera geometry injection plus curriculum training to produce consistent cross-view videos from flexible agent counts.
DisCo uses discrete action primitives for camera control in video world models to achieve more reliable action following than continuous trajectories.
WorldFly integrates a world model into a VLA framework via dual-branch coupled flow matching to jointly generate future videos and actions, outperforming baselines on an urban canyon traversal benchmark especially in unseen environments.
GIM-World adds a camera-queryable geometry distillation head and pruning rule to implicit memory in video world models, claiming better long-horizon geometric consistency on the MIND benchmark than explicit and implicit baselines.
Proposes World-Ego Modeling with WEM using CP-MoE diffusion and a new HTEWorld benchmark, claiming SOTA on hybrid navigation-manipulation tasks.
Pyramid Forcing classifies attention heads into Anchor, Wave, and Veil types and applies type-specific KV cache policies to improve long-horizon autoregressive video generation quality.
RealCam is a causal autoregressive model for real-time camera-controlled video-to-video generation, using cross-frame in-context teacher distillation and loop-closed data augmentation to achieve high fidelity and consistency.
LongLive is a causal autoregressive video generator that produces up to 240-second interactive videos at 20.7 FPS on one H100 GPU after 32 GPU-days of fine-tuning from a 1.3B short-clip model.
A video world model framework that uses LLM-orchestrated 3D trajectories as control signals for generation to achieve persistent dynamic object memory and viewpoint freedom.
WorldOlympiad is a new benchmark decomposing world-model evaluation into physical, geometry, and interaction tracks using segmentation, MLLM judges, Gaussian splatting, and action prompts on diverse scenarios.
WorldCraft introduces NWT, SP-LoRA, and TASP to enable object trajectory control in video-based world models while preserving camera navigation.
Matrix-Game 2.0 introduces a scalable data pipeline, action-injection module, and few-step distillation to enable real-time streaming video generation at 25 FPS from game-engine interactions, with open-sourced weights and code.
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WorldFly: A World-Model-Based Vision-Language-Action Model for UAV Navigation
WorldFly integrates a world model into a VLA framework via dual-branch coupled flow matching to jointly generate future videos and actions, outperforming baselines on an urban canyon traversal benchmark especially in unseen environments.