Visual Generation Interview Questions: 2026 Extended Edition is a comprehensive interview preparation guide for modern visual generation. It covers the key technical areas of diffusion models, flow matching, visual autoregressive generation, video generation, 3D/4D generation, controllable generation, post-training, verifier-based optimization, agentic image generation, world modeling, and generation system engineering.
 
This book contains 100 carefully designed interview questions. It includes both foundational topics such as DDPM, DDIM, DPM-Solver, Latent Diffusion, Classifier-Free Guidance, ControlNet, and LoRA, as well as advanced 2026 topics such as Pixel MeanFlow, SubFlow, Flow-GRPO, visual generation post-training, visual verifiers, agentic image generation, end-to-end visual tokenizers, agentic world modeling, and real-time multimodal generation systems.
 
Each question is structured with intuitive explanations, mathematical derivations, notation clarification, follow-up interview questions, common failure modes, and concise summaries. The goal is not only to help readers memorize answers, but also to build a deep and systematic understanding of how visual generation technologies are evolving.
 
This guide is ideal for:
Candidates preparing for AI Research Scientist, Applied Scientist, Machine Learning Engineer, Multimodal AI Engineer, or Generative AI roles;
Researchers and students studying diffusion models, flow-based generation, AR visual generation, video generation, and world models;
Professionals who want to quickly understand the latest visual generation trends and express them clearly in technical interviews;
Anyone preparing for English technical interviews in generative AI.
 
Rather than being a simple collection of questions, this book provides a structured roadmap for understanding how visual generation is moving from image synthesis to video generation, multimodal interaction, post-training optimization, and agentic world modeling.