Verifiable Visual Rewards Transfer from Synthetic Scenes to Natural Prompts
cs.AI, cs.CV
Submitted: 2026-09-28
Updated: 2026-09-28
Code: https://github.com/stellalisy/VVRBenchhttps:
Terminology
Sources
- DeTikZify: Synthesizing Graphics Programs for Scientific Figures and Sketches with TikZ
- Training Diffusion Models with Reinforcement Learning
- HiDream-I1: A High-Efficient Image Generative Foundation Model with Sparse Diffusion Transformer
- Enigmata: Scaling Logical Reasoning in Large Language Models with Synthetic Verifiable Puzzles
- MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge for Text-to-Image Generation?
- Davidsonian Scene Graph: Improving Reliability in Fine-grained Evaluation for Text-to-Image Generation
- Diagnostic Benchmark and Iterative Inpainting for Layout-Guided Image Generation
- Directly Fine-Tuning Diffusion Models on Differentiable Rewards
- Scaling Rectified Flow Transformers for High-Resolution Image Synthesis
- DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models
- DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
- CLIPScore: A Reference-free Evaluation Metric for Image Captioning
- Understanding Reward Hacking in Text-to-Image Reinforcement Learning
- ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment
- TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question Answering
- T2I-CompBench++: An Enhanced and Comprehensive Benchmark for Compositional Text-to-image Generation
- AlphaGRPO: Unlocking Self-Reflective Multimodal Generation in UMMs via Decompositional Verifiable Reward
- CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning
- Evaluating Numerical Reasoning in Text-to-Image Models
- GenEval 2: Addressing Benchmark Drift in Text-to-Image Evaluation
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