Omni-Reward: Towards Generalist Omni-Modal Reward Modeling with Free-Form Preferences
Chinese Academy of Sciences
Research using Rapidata
The research community builds on Rapidata.
Reward models, preference optimization, AI-image detection and video evaluation: researchers train and test their models on human judgments collected with Rapidata, from our open datasets on Hugging Face or from studies run directly on the platform.
24
Peer-reviewed papers building on Rapidata
143
Researchers across the author lists
8
Rapidata open datasets in use
Published at
With authors from NVIDIA, ByteDance, Alibaba, Tencent Hunyuan, UIUC, Columbia University and 27 more institutions.
UnifiedReward-Think: Unified Multimodal Chain-of-Thought Reward Model through Reinforcement Fine-Tuning
Tencent Hunyuan · Fudan University · Shanghai AI Lab
Factuality Matters: When Image Generation and Editing Meet Structured Visuals
CUHK MMLab · Hugging Face · ByteDance +3
PICABench: How Far Are We from Physically Realistic Image Editing?
Shanghai AI Lab · CUHK MMLab · Krea AI +2
Q-Sched: Pushing the Boundaries of Few-Step Diffusion Models with Quantization-Aware Scheduling
UT Austin
SIPO: Stabilized and Improved Preference Optimization for Aligning Diffusion Models
Fudan University · University of Adelaide
Accelerating Masked Image Generation by Learning Controlled Latent Dynamics
Shanghai AI Lab · Shanghai Jiao Tong University
MSRL: Scaling Generative Multimodal Reward Modeling via Multi-Stage Reinforcement Learning
ByteDance · Northeastern University
FakeXplain: Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs
Shanghai Jiao Tong University · Ant Group
VR-Thinker: Boosting Video Reward Models through Thinking-with-Image Reasoning
Kuaishou Kling · CUHK MMLab · Nanjing University
PhyProbe: Rethinking Physical Consistency Evaluation in Generated Videos
NVIDIA · University of Waterloo · Vector Institute
Plan-and-Verify Video Reward Reasoning with Spatio-Temporal Scene Graph Grounding
Korea University
RationalRewards: Reasoning Rewards Scale Visual Generation Both Training and Test Time
University of Waterloo · HKUST · Alibaba
DCPO: Dual Caption Preference Optimization for Diffusion Models
Arizona State University
Lumina-Image 2.0: A Unified and Efficient Image Generative Framework
Shanghai AI Lab · CUHK · Krea AI +1
GeoPair: Geometry-Preserving Cross-Layer Factorization for Training-Free Transformer Compression
MWS AI · ITMO University
PropaInsight: Toward Deeper Understanding of Propaganda in Terms of Techniques, Appeals, and Intent
UIUC · Columbia University · MBZUAI
Gaze patterns predict preference and confidence in pairwise AI image evaluation
Columbia University
GAMMA: Generalizable AI-Generated Image Detection via Multi-Task and Manipulation-Augmented Supervision
Shanghai Jiao Tong University · Ant Group
A Zipfian Analysis of Visual Token Distributions for AI-Generated Images
Keio University
Papers citing our research
These papers build on our published findings rather than using Rapidata data or the platform directly.
- CVPR 2025KAIST · Adobe Research
Visual Persona: Foundation Model for Full-Body Human Customization
- ICML 2025Mila · Université de Montréal
LIVS: A Pluralistic Alignment Dataset for Inclusive Public Spaces
- ICCV 2025KAIST · Hyundai Mobis
AM-Adapter: Appearance Matching Adapter for Exemplar-based Semantic Image Synthesis in-the-Wild
- ISMIR 2025Shanghai Jiao Tong University · Shanghai AI Lab · Tsinghua University
A Survey on Vision-to-Music Generation: Methods, Datasets, Evaluation, and Challenges
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