Self-correction Optimization for Interleaved Multimodal Generation
cs.CV
Submitted: 2026-10-07
Updated: 2026-10-07
Comments: 20 pages, 10 figures
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- Cosmos 3: Omnimodal World Models for Physical AI
- LLaDA2.0-Uni: Unifying Multimodal Understanding and Generation with Diffusion Large Language Model
- World Simulation with Video Foundation Models for Physical AI
- OpenLEAF: Open-Domain Interleaved Image-Text Generation and Evaluation
- ANOLE: An Open, Autoregressive, Native Large Multimodal Models for Interleaved Image-Text Generation
- Emerging Properties in Unified Multimodal Pretraining
- SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture
- Vision as Unified Multimodal Generation
- Classifier-Free Diffusion Guidance
- Imagen Video: High Definition Video Generation with Diffusion Models
- Video Diffusion Models
- Breaking Dual Bottlenecks: Evolving Unified Multimodal Models into Self-Adaptive Interleaved Visual Reasoners
- VideoWorld 2: Learning Transferable Knowledge from Real-world Videos
- DuoGen: Towards General Purpose Interleaved Multimodal Generation
- Chameleon: Mixed-Modal Early-Fusion Foundation Models
- MM-Interleaved: Interleaved Image-Text Generative Modeling via Multi-modal Feature Synchronizer
- Emu3: Next-Token Prediction is All You Need
- Wan-Weaver: Interleaved Multi-modal Generation via Decoupled Training
- MiniGPT-5: Interleaved Vision-and-Language Generation via Generative Vokens
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