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Professional furnishing knowledge can be directly learned and applied to generate constraint-aware furniture layouts, bypassing costly iterative agentic inference.
Pre-trained vision encoders are shockingly bad at distinguishing identity when background context is controlled, but a simple contrastive learning scheme can fix it.
