TASTE supplies designer multi-dimensional rankings of T2I graphic outputs with statistical validation showing moderate agreement and benchmarks where a TASTE-trained MLP outperforms off-the-shelf VLMs.
ImagenWorld: Stress-testing image generation models with explainable human evaluation on open-ended real-world tasks
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RewardHarness self-evolves a tool-and-skill library from 100 preference examples to reach 47.4% accuracy on image-edit evaluation, beating GPT-5, and yields stronger RL-tuned models.
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TASTE: A Designer-Annotated Multi-Dimensional Preference Dataset for AI-Generated Graphic Design
TASTE supplies designer multi-dimensional rankings of T2I graphic outputs with statistical validation showing moderate agreement and benchmarks where a TASTE-trained MLP outperforms off-the-shelf VLMs.
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RewardHarness: Self-Evolving Agentic Post-Training
RewardHarness self-evolves a tool-and-skill library from 100 preference examples to reach 47.4% accuracy on image-edit evaluation, beating GPT-5, and yields stronger RL-tuned models.