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Achieving an FID of 1.45 in just 600 epochs, Energy-Guided Flow Matching redefines efficiency in high-quality image generation without the need for extensive model adaptations.
iFAN boosts segmentation accuracy by aligning query competition with mask quality, achieving significant performance gains without extra computational overhead.
Spatial hallucinations in 3D generation can be effectively mitigated using a model-agnostic framework that leverages multimodal language models for consistency optimization.
