Curvature-Guided Mixing for MLLM Adaptation
arXiv:2606.24963v1 Announce Type: new Abstract: Fine-tuning Multimodal Large Language Models (MLLMs) on specialized tasks often leads to catastrophic forgetting of their general capabilities. Existing model merging methods to combat this are often heuristic or use sub-optimal objectives. We propose CurvatureGuided Mixing (CGM), a theoretically grounded framework that merges pre-trained and fine-tuned models. CGM formulates a joint optimization objective and uses a second-order (Hessian) approxim...
arXiv cs.CV
·Jinglong Yang, Jiaxuan He, Wenjian Huang, Zhan Zhuang, Jianguo Zhang
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