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ToolMATH reveals that long-range planning and coherent observation usage are more critical for tool-augmented LLMs than simply improving local action selection.
Ditch the hand-crafted priors: SEAL-pose learns a data-driven loss function that significantly boosts 3D human pose estimation by enforcing structural consistency, outperforming models with explicit constraints.
