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Mitigating Task Objective Conflicts for Continual Learning in Unified Multimodal Models
Recent advances in unified autoregressive (AR) models have enabled multimodal understanding (MMU) and text-to-image generation (T2I) within a single architecture. However, in continual learning settings, their divergent objectives can induce task interference, hindering knowledge preservation and ad
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