Human Preference Evaluation on ImageReward (test)
0.675Preference AccuracyMPS
Evaluation Results
| Method | Links | |
|---|---|---|
| MPSTrained on=MHP datasets2024.05 | 0.675 | |
| MPS2026.05 | 0.675 | |
| HPSv3Backbone=Qwen2VL-7B2026.02 | 0.6703 | |
| HPSv3 - 7B2026.05 | 0.668 | |
| MPSBackbone=CLIP2026.02 | 0.6637 | |
| HPS v2Pre-trained=true2024.05 | 0.657 | |
| HPSv22026.05 | 0.657 | |
| HPSv2Backbone=CLIP2026.02 | 0.6562 | |
| ImageRewardBackbone=CLIP2026.02 | 0.6515 | |
| ImageRewardPre-trained=true2024.05 | 0.651 | |
| ImageReward2026.05 | 0.651 | |
| DRMWeights=Pre-trained, Epoch=1, Size=5122026.05 | 0.641 | |
| UnifiedRewardBackbone=LLaVA-OV-7B2026.02 | 0.6382 | |
| PickScorePre-trained=true2024.05 | 0.629 | |
| DRMWeights=Pre-trained, Epoch=1, Size=2562026.05 | 0.629 | |
| PickScoreBackbone=CLIP2026.02 | 0.6273 | |
| DiNa-LRMBackbone=SD3.5-M-2B, Multi-noise inference scaling=true2026.02 | 0.6175 | |
| PickScore2026.05 | 0.616 | |
| HPSPre-trained=true2024.05 | 0.612 | |
| HPS2026.05 | 0.612 | |
| LRM-SDXLBackbone=SDXL2026.02 | 0.6035 | |
| DiNa-LRMBackbone=SD3.5-M-2B, Multi-noise inference scaling=false2026.02 | 0.6034 | |
| LRM-SD1.5Backbone=SD-1.52026.02 | 0.5917 | |
| UnifiedReward-ThinkBackbone=LLaVA-OV-7B2026.02 | 0.5854 | |
| HPSv3 - 2B2026.05 | 0.579 | |
| Aesthetic ScorePre-trained=true2024.05 | 0.574 | |
| Aesthetic Score Predictor2026.05 | 0.574 | |
| CLIP ViT-H/142026.05 | 0.571 | |
| CLIP scorePre-trained=true2024.05 | 0.543 | |
| DRMWeights=Random, Epoch=3, Size=2562026.05 | 0.537 | |
| DRMWeights=Random, Epoch=1, Size=2562026.05 | 0.524 | |
| DRMWeights=Random, Epoch=2, Size=2562026.05 | 0.519 |