DiVid: Diagnosing Dimension-Specific Diversity Collapse in Video Generation Models

arXiv:2610.01661 · cs.CV · Submitted 2026-10-01 · Read on arXiv

cs.CV

Submitted: 2026-10-01

Updated: 2026-10-01

Terminology

• Benchmark — 18× in this paper · explained in 2 episodes
• Diffusion Model — 11× in this paper · explained in 8 episodes
• Diffusion Models — 11× in this paper · explained in 6 episodes
• Homogenization — 10× in this paper · explained in 2 episodes
• Fidelity — 8× in this paper · explained in 2 episodes
• Aggregation — 6× in this paper · explained in 1 episode
• Alignment — 6× in this paper · explained in 1 episode
• Generative Model — 6× in this paper · explained in 2 episodes
• Generative Models — 6× in this paper · explained in 2 episodes
• Consistency — 5× in this paper · explained in 3 episodes
• Core — 5× in this paper · explained in 2 episodes
• Generative AI — 5× in this paper · explained in 2 episodes
• Instruction Faithfulness — 5× in this paper
• Mode Collapse — 4× in this paper · explained in 2 episodes
• Robustness — 4× in this paper · explained in 5 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Embeddings — 3× in this paper · explained in 2 episodes
• Failure Modes — 3× in this paper · explained in 3 episodes
• Hallucination — 3× in this paper · explained in 3 episodes
• Optical Flow — 3× in this paper · explained in 2 episodes
• Verification — 3× in this paper · explained in 2 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Benchmarking — 2× in this paper · explained in 3 episodes
• GRPO — 2× in this paper · explained in 6 episodes
• Homogeneity — 2× in this paper · explained in 2 episodes
• Motion Smoothness — 2× in this paper
• Accountability — 1× in this paper · explained in 2 episodes
• Aesthetic Quality — 1× in this paper
• Annotator Agreement — 1× in this paper · explained in 1 episode
• Decoupling — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Personalization — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Temporal consistency — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• VBench Temporal Flickering — 1× in this paper
• World Model — 1× in this paper · explained in 7 episodes

Sources

• Benchmarking Diversity in Image Generation via Attribute-Conditional Human Evaluation
• Consistency-diversity-realism Pareto fronts of conditional image generative models
• Qwen3-VL Technical Report
• Evolution of Video Generative Foundations
• Consistency-Preserving Diverse Video Generation
• OrthoMotion:Disentangling Camera and Subject Motion via Geometry Semantics Orthogonal Attention
• VEAT Quantifies Implicit Associations in Text-to-Video Generator Sora and Reveals Challenges in Bias Mitigation
• Seedance 1.5 pro: A Native Audio-Visual Joint Generation Foundation Model
• Wan: Open and Advanced Large-Scale Video Generative Models
• ATI: Any Trajectory Instruction for Controllable Video Generation
• Directing the World: Fast Autoregressive Video Generation with Compositional Human-Camera Control
• HunyuanVideo 1.5 Technical Report
• VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness
• FAIRT2V: Training-Free Debiasing for Text-to-Video Diffusion Models
• Is Sora a World Simulator? A Comprehensive Survey on General World Models and Beyond

Related papers

• Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
• AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
• Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
• MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
• TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
• A Survey on Efficient Vision-Language-Action Models