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KeepLoRA++ reveals that effective continual learning hinges on strategically managing knowledge across different layers of a model, leading to significant performance gains in complex tasks.
By learning to prioritize edges based on global consistency, this method constructs more reliable and compact pose graphs for Structure-from-Motion, outperforming traditional nearest neighbor retrieval, especially in ambiguous scenes.
