Through the PRISM: Preference Representation in Intermediate States of Video Diffusion Models
cs.CV
Submitted: 2026-06-18
Updated: 2026-10-12
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Qwen2.5-VL Technical Report
- Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets
- SkyReels-V2: Infinite-length Film Generative Model
- Seedance 1.0: Exploring the Boundaries of Video Generation Models
- VideoScore: Building Automatic Metrics to Simulate Fine-grained Human Feedback for Video Generation
- HunyuanVideo: A Systematic Framework For Large Video Generative Models
- LLaVA-OneVision: Easy Visual Task Transfer
- Video-T1: Test-Time Scaling for Video Generation
- Improving Video Generation with Human Feedback
- Decoupled Weight Decay Regularization
- Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps
- Inference-Time Text-to-Video Alignment with Diffusion Latent Beam Search
- Scalable Diffusion Models with Transformers
- Proximal Policy Optimization Algorithms
- A General Framework for Inference-time Scaling and Steering of Diffusion Models
- Llama 2: Open Foundation and Fine-Tuned Chat Models
- Wan: Open and Advanced Large-Scale Video Generative Models
- Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
- LiFT: Leveraging Human Feedback for Text-to-Video Model Alignment
- Unified Reward Model for Multimodal Understanding and Generation
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