APT: Feedback-Driven Agentic Post-Training for Text-to-Image Generation
cs.CV, cs.AI
Submitted: 2026-10-13
Updated: 2026-10-13
Code: https://github.com/black-forest-labs/flux
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- Lens: Rethinking Training Efficiency for Foundational Text-to-Image Models
- Unified Text-Image Generation with Weakness-Targeted Post-Training
- Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling
- Gen-Searcher: Reinforcing Agentic Search for Image Generation
- X-Omni: Reinforcement Learning Makes Discrete Autoregressive Image Generative Models Great Again
- Mind-Brush: Integrating Agentic Cognitive Search and Reasoning into Image Generation
- ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment
- GenAgent: Scaling Text-to-Image Generation via Agentic Multimodal Reasoning
- GenEval 2: Addressing Benchmark Drift in Text-to-Image Evaluation
- Curriculum Group Policy Optimization: Adaptive Sampling for Unleashing the Potential of Text-to-Image Generation
- MixGRPO: Unlocking Flow-based GRPO Efficiency with Mixed ODE-SDE
- Aesthetic Post-Training Diffusion Models from Generic Preferences with Step-by-step Preference Optimization
- Proximal Policy Optimization Algorithms
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation
- LongCat-Image Technical Report
- ImAgent: A Unified Multimodal Agent Framework for Test-Time Scalable Image Generation
- Qwen-Image-2.0-RL Technical Report
- Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation
- Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing
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