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Model merging in llms, mllms, and beyond: Methods, theories, applications and opportunities
Model merging is an efficient empowerment technique in the machine learning community
that does not require the collection of raw training data and does not require expensive …
that does not require the collection of raw training data and does not require expensive …
Mediator: Memory-efficient LLM Merging with Less Parameter Conflicts and Uncertainty Based Routing
Model merging aggregates Large Language Models (LLMs) finetuned on different tasks into
a stronger one. However, parameter conflicts between models leads to performance …
a stronger one. However, parameter conflicts between models leads to performance …