SkillPE: Creativity-Oriented Cinematic Skill Evolution for Text-to-Video Prompt Engineering

arXiv:2609.34335 · cs.CV, cs.AI · Submitted 2026-09-28 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-09-28

Updated: 2026-09-28

Terminology

• Benchmark — 21× in this paper · explained in 2 episodes
• Fidelity — 19× in this paper · explained in 2 episodes
• Prompt Engineering — 16× in this paper · explained in 4 episodes
• Narrative Appeal — 13× in this paper
• Alignment — 12× in this paper · explained in 1 episode
• Cinematic Quality — 12× in this paper
• Core — 11× in this paper · explained in 2 episodes
• Ablation — 10× in this paper · explained in 1 episode
• Prompt Fidelity — 8× in this paper
• Adaptation — 5× in this paper · explained in 1 episode
• Ablation study — 4× in this paper · explained in 1 episode
• Consistency — 4× in this paper · explained in 3 episodes
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Multi-Agent System — 2× in this paper · explained in 6 episodes
• Multi-agent Collaboration — 2× in this paper · explained in 2 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Adaptability — 1× in this paper · explained in 1 episode
• Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 1× in this paper
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 3 episodes
• Model-Agnostic — 1× in this paper · explained in 2 episodes
• Multi-Agent Framework — 1× in this paper · explained in 3 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Self-Evolving Agents — 1× in this paper · explained in 2 episodes
• Semantic Similarity — 1× in this paper · explained in 2 episodes
• Steering — 1× in this paper · explained in 2 episodes

Sources

• EvoSkill: Automated Skill Discovery for Multi-Agent Systems
• GenEvolve: Self-Evolving Image Generation Agents via Tool-Orchestrated Visual Experience Distillation
• NEWTON: Agentic Planning for Physically Grounded Video Generation
• Mind-Brush: Integrating Agentic Cognitive Search and Reasoning into Image Generation
• StoryAgent: Customized Storytelling Video Generation via Multi-Agent Collaboration
• GenAgent: Scaling Text-to-Image Generation via Agentic Multimodal Reasoning
• SkillNet: Create, Evaluate, and Connect AI Skills
• VISTA: A Test-Time Self-Improving Video Generation Agent
• A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications
• Seedance 2.0: Advancing Video Generation for World Complexity
• VQQA: An Agentic Approach for Video Evaluation and Quality Improvement
• Kling-Omni Technical Report
• Voyager: An Open-Ended Embodied Agent with Large Language Models
• Reinforcement Learning for Self-Improving Agent with Skill Library
• Automated Movie Generation via Multi-Agent CoT Planning
• SkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement Learning
• AutoSkill: Experience-Driven Lifelong Learning via Skill Self-Evolution
• Mora: Enabling Generalist Video Generation via A Multi-Agent Framework
• SkillWeaver: Web Agents can Self-Improve by Discovering and Honing Skills
• VideoAgent: All-in-One Framework for Video Understanding and Editing

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