HiPhy: Hierarchical Alignment for Physically-Plausible Multi-Principle Video Generation

arXiv:2610.02197 · cs.CV · Submitted 2026-10-01 · Read on arXiv

cs.CV

Submitted: 2026-10-01

Updated: 2026-10-01

Project page: https://hiphy-video.github.io

Terminology

• Alignment — 39× in this paper · explained in 1 episode
• Benchmark — 14× in this paper · explained in 2 episodes
• Ablation — 10× in this paper · explained in 1 episode
• GRPO — 9× in this paper · explained in 6 episodes
• Semantic Alignment — 9× in this paper · explained in 3 episodes
• Diffusion Model — 7× in this paper · explained in 8 episodes
• Diffusion Models — 7× in this paper · explained in 6 episodes
• Fidelity — 6× in this paper · explained in 2 episodes
• Reinforcement Learning — 5× in this paper · explained in 4 episodes
• Failure Modes — 3× in this paper · explained in 3 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Adam — 2× in this paper · explained in 2 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Embodied AI — 2× in this paper · explained in 2 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• GRPO Objective — 2× in this paper · explained in 2 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Momentum transfer — 2× in this paper · explained in 2 episodes
• Pseudo-labels — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Verifier — 2× in this paper · explained in 2 episodes
• World Model — 2× in this paper · explained in 7 episodes
• Alignment Problem — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Flow Matching — 1× in this paper · explained in 8 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Prompt Adherence — 1× in this paper · explained in 2 episodes
• Provenance — 1× in this paper · explained in 3 episodes
• Structural Integrity — 1× in this paper · explained in 3 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• World Simulation with Video Foundation Models for Physical AI
• Qwen Technical Report
• VideoPhy-2: A Challenging Action-Centric Physical Commonsense Evaluation in Video Generation
• PhyGDPO: Physics-Aware Groupwise Direct Preference Optimization for Physically Consistent Text-to-Video Generation
• "PhyWorldBench": A Comprehensive Evaluation of Physical Realism in Text-to-Video Models
• Imagen Video: High Definition Video Generation with Diffusion Models
• Video Diffusion Models
• Planning with Sketch-Guided Verification for Physics-Aware Video Generation
• Self-Refining Video Sampling
• How Far is Video Generation from World Model: A Physical Law Perspective
• Adam: A Method for Stochastic Optimization
• Epipolar Geometry Improves Video Generation Models
• PISA Experiments: Exploring Physics Post-Training for Video Diffusion Models by Watching Stuff Drop
• Flow Matching for Generative Modeling
• Improving Video Generation with Human Feedback
• Compositional Visual Generation with Composable Diffusion Models
• GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL Optimization
• Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• FlowMo: Variance-Based Flow Guidance for Coherent Motion in Video Generation

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