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Neglecting the structural differences in candidate negatives can lead to suboptimal recommendations, but SAHC-NS adapts to these variations, enhancing sample quality and model performance.
Anomalies in text-attributed graphs can be detected more effectively by aligning textual semantics with graph topology, revealing insights that traditional methods overlook.
GRPO's Achilles' heel in deep search is its coarse advantage assignment, but CalibAdv offers a way to surgically correct it, boosting both performance and training stability.
Reviving degraded opera videos gets a boost: TextOVSR leverages text prompts to guide super-resolution, outperforming state-of-the-art methods by explicitly modeling both degradation and content semantics.
