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Nima Jamali

2 accepted papers

2026

ImagenWorld: Stress-Testing Image Generation Models with Explainable Human Evaluation on Open-ended Real-World Tasks

ICLR 2026poster

Advances in diffusion, autoregressive, and hybrid models have enabled high-quality image synthesis for tasks such as text-to-image, editing, and reference-guided composition. Yet, existing benchmarks remain limited, either focus on isolated tasks, cover only narrow domains, or provide opaque scores…

Cited by 0SourcecodeScholar
2026

Training-Free Distribution Adaptation for Diffusion Models via Maximum Mean Discrepancy Guidance

ICML 2026poster

Pre-trained diffusion models have emerged as powerful generative priors for both unconditional and conditional sample generation, yet their outputs often deviate from the characteristics of user-specific target data. Such mismatches are especially problematic in domain adaptation tasks, where only a…

Cited by 0SourceScholar