C^2GR uses Bayesian Joint Diffusion for coupled image-mask synthesis and Relation-aware Unified Prompt Synchronization to reduce forgetting in continual universal segmentation, showing a 2.44% performance drop versus joint training on 20 tasks.
Medseqft: Sequential fine-tuning foundation models for 3d medical im- age segmentation.arXiv preprint arXiv:2509.06096, 2025
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C^2GR: Coupled Comprehensive Generative Replay for a Continually Learnable Universal Segmentation Model
C^2GR uses Bayesian Joint Diffusion for coupled image-mask synthesis and Relation-aware Unified Prompt Synchronization to reduce forgetting in continual universal segmentation, showing a 2.44% performance drop versus joint training on 20 tasks.