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LLM multi-agent systems can achieve significantly higher accuracy at a fraction of the cost by learning to selectively delegate tasks instead of relying on rigid orchestration.
Frame-by-frame image enhancement can actually *hurt* 3D reconstruction, but Dehaze-then-Splat shows how physics-informed regularization can turn this liability into an asset for novel view synthesis.
