MFFM chains residual-calibrated flow matching steps across fidelity levels, conditioning each on the low-fidelity input so that L deterministic network evaluations produce a fine-grid PDE solution.
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HEaD+ detects object hallucinations early in diffusion generation via cross-attention maps, text, and a Predicted Final Image, raising complete image rates by 6-8% for four-object prompts and reducing time by up to 32%.
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Multi-Fidelity Flow Matching: Cascaded Refinement of PDE Solutions
MFFM chains residual-calibrated flow matching steps across fidelity levels, conditioning each on the low-fidelity input so that L deterministic network evaluations produce a fine-grid PDE solution.
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Hallucination Early Detection in Diffusion Models
HEaD+ detects object hallucinations early in diffusion generation via cross-attention maps, text, and a Predicted Final Image, raising complete image rates by 6-8% for four-object prompts and reducing time by up to 32%.