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LLMs can now capture an author's unique voice in translations, thanks to a multi-agent system guided by a "Stylistic Feature Spectrum" derived from wavelet transforms.
Cycle consistency unlocks SOTA cross-view object correspondence in videos without ground-truth annotations, even enabling test-time training.
