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UXBench reveals that LLMs vary dramatically in their ability to produce actionable UX critiques, challenging the assumption of uniform model performance in this domain.
By intelligently fusing heterogeneous guidance cues, HAFMat achieves unprecedented accuracy in estimating human materials from a single image.
Continuous-target modeling reveals a shared semantic mapping for ASR and S2TT, challenging conventional views on their error sources.
