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awesome-model-merging-methods-theories-applications

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Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. ACM Computing Surveys, 2026.

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💥 News 💥SurveyBenchmark/EvaluationAdvanced MethodsApplication of Model Merging in Foundation ModelsApplication of Model Merging in Different Machine Learning SubfieldsOther Applications

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Advanced Methods

1bit-Merging: Dynamic Quantized Merging for Large Language ModelsDuring Merging Methods
2025
Acceleration of stochastic approximation by averagingDuring Merging Methods
1992
Access Sets Matter: Budgeting Expert Reads for Scalable Weight-Space Model MergingOther Merging Methods
2026
Accurate and Efficient Low-Rank Model Merging in Core SpaceDuring Merging Methods
2025
ACE-Merging: Data-Free Model Merging with Adaptive Covariance EstimationOther Merging Methods
2026
Activated Parameter Locating via Causal Intervention for Model MergingDuring Merging Methods
2024

Application of Model Merging in Foundation Models

3DM: Distill, Dynamic Drop, and Merge for Debiasing Multi-modal Large Language ModelsModel Merging in Large Language Models
2025
ABC: Towards a Universal Code Styler through Model MergingModel Merging in Large Language Models
2025
AdaLTM: Adaptive Layer-wise Task Vector Merging for Categorical Speech Emotion Recognition with ASR Knowledge IntegrationModel Merging in Large Language Models
2026
AdaMMS: Model Merging for Heterogeneous Multimodal Large Language Models with Unsupervised Coefficient OptimizationModel Merging in Multimodal Large Language Models
2025
Adapting Chat Language Models Using Only Target Unlabeled Language DataModel Merging in Large Language Models
2025
Adapting Multilingual Models to Code-Mixed Tasks via Model MergingModel Merging in Large Language Models
2025

Other Applications

Application of Model Merging in Different Machine Learning Subfields

AdaMergeX: Cross-Lingual Transfer with Large Language Models via Adaptive Adapter MergingModel Merging in Zero-shot/Few-shot Learning
2024
AdaMerging: Adaptive Model Merging for Multi-Task LearningModel Merging in Multi-Task/Multi-Objective/Multi-Domain/Auxiliary Learning
2024
Adapter Merging with Centroid Prototype Mapping for Scalable Class-Incremental LearningModel Merging in Continual Learning
2024
AdapterSoup: Weight Averaging to Improve Generalization of Pretrained Language ModelsModel Merging in Out-of-Distribution/Domain Generalization
2023
Adaptive Discovering and Merging for Incremental Novel Class DiscoveryModel Merging in Continual Learning
2024
Adaptive LoRA Merging for Efficient Domain Incremental LearningModel Merging in Continual Learning
2024

Benchmark/Evaluation

Survey

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