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Hidden-state representation alignment in diffusion models isn't just an empirical heuristic鈥攊t is mathematically equivalent to score distillation operating directly within the latent representation space.
Machine translation benchmarks have functionally saturated, but pairing human-authored failure cases with deterministic verification rules reveals critical multimodal blind spots that automated metrics consistently miss.
Foundation models are revolutionizing monocular depth estimation, achieving unprecedented accuracy and robustness in real-world applications.
