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PhysCaP enables robots to actively infer hidden physical properties, achieving superior manipulation efficiency without additional sensors.
Grounding image dehazing in the physics of haze formation allows HNDiff to achieve unprecedented restoration quality, outperforming traditional methods.
DDTNet reveals that focusing on degradation transfer can dramatically improve image restoration performance across diverse weather conditions.
SpatialClaw enables agents to dynamically compose and adapt their reasoning strategies, achieving a remarkable 11.2-point accuracy boost over traditional spatial agents.
