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Explicitly modeling human-object interactions boosts multi-person human mesh recovery accuracy by up to 9.9%, showing that interaction context is key to understanding human pose and shape in complex scenes.
Medical MLLMs, despite their size and training data, stumble on basic image classification due to four key failure modes, revealing a disconnect between hype and clinical readiness.
