CineForge: Self-Improving Agents for Long-Horizon Video Generation

arXiv:2608.29621 · cs.CV, cs.AI · Submitted 2026-08-30 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-08-30

Updated: 2026-08-30

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Alignment — 29× in this paper · explained in 1 episode
• Benchmark — 21× in this paper · explained in 2 episodes
• Consistency — 14× in this paper · explained in 3 episodes
• Aggregation — 11× in this paper · explained in 1 episode
• Trace — 11× in this paper · explained in 2 episodes
• Calibration — 8× in this paper · explained in 7 episodes
• Provenance — 8× in this paper · explained in 3 episodes
• Abstention — 7× in this paper · explained in 1 episode
• Causal State — 7× in this paper
• Character Arc — 7× in this paper
• Directorial Orchestration — 7× in this paper
• Pacing and Resource Allocation — 6× in this paper
• Adaptation — 5× in this paper · explained in 1 episode
• Case-to-Pattern-to-Policy Evolution — 5× in this paper
• Benchmarking — 3× in this paper · explained in 3 episodes
• Fidelity — 3× in this paper · explained in 2 episodes
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• Agent Skills — 1× in this paper · explained in 1 episode
• Agentic Framework — 1× in this paper · explained in 6 episodes
• Agentic System — 1× in this paper · explained in 2 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Domain Shift — 1× in this paper · explained in 4 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Multi-agent Collaboration — 1× in this paper · explained in 2 episodes
• Temporal consistency — 1× in this paper · explained in 2 episodes

Sources

• DemoEvolve: Overcoming Sparse Feedback in Agentic Harness Evolution with Demonstrations
• DirectorBench: Diagnosing Long-Form Video Generation with Personalized Multi-Agent Evaluation
• From Failed Trajectories to Reliable LLM Agents: Diagnosing and Repairing Harness Flaws
• TaleCrafter: Interactive Story Visualization with Multiple Characters
• MAPGD: Multi-Agent Prompt Gradient Descent for Collaborative Prompt Optimization
• EntityBench: Towards Entity-Consistent Long-Range Multi-Shot Video Generation
• Automated Design of Agentic Systems
• GenMAC: Compositional Text-to-Video Generation with Multi-Agent Collaboration
• ViMax: Agentic Video Generation
• VBench: Comprehensive Benchmark Suite for Video Generative Models
• VBench++: Comprehensive and Versatile Benchmark Suite for Video Generative Models
• DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines
• AgentX: Towards Agent-Driven Self-Iteration of Industrial Recommender Systems
• StoryGAN: A Sequential Conditional GAN for Story Visualization
• VideoDirectorGPT: Consistent Multi-scene Video Generation via LLM-Guided Planning
• Agentic Harness Engineering: Observability-Driven Automatic Evolution of Coding-Agent Harnesses
• Harness Updating Is Not Harness Benefit: Disentangling Evolution Capabilities in Self-Evolving LLM Agents
• Advancing Narrative Long Video Generation via Training-Free Identity-Aware Memory
• LongAV-Compass: Towards Unified Evaluation of Minute-Scale Audio-Visual Generation Across T2AV, I2AV, and V2AV
• VISTA: A Test-Time Self-Improving Video Generation Agent

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