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CAMFT: Conflict-Aware Mergeable Fine-Tuning for Large Language Models
Model merging has emerged as a promising paradigm for integrating multiple task-specific capabilities into a single large language model. However, existing methods predominantly focus on post-hoc processing of independently fine-tuned models, overlooking how the training phase itself impacts cross-t
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