model merging

Gemel: Model Merging for Memory-Efficient, Real-Time Video Analytics at the Edge NSDI 2023 Git Re-Basin: Merging Models modulo Permutation Symmetries ICLR 2023 MAS: Towards Resource-Efficient Federated Multiple-Task Learning ICCV 2023 Merging Experts into One: Improving Computational Efficiency of Mixture of Experts EMNLP 2023 Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization ICML 2023 Recyclable Tuning for Continual Pre-training ACL 2023 Structured Federated Learning through Clustered Additive Modeling NeurIPS 2023 TIES-Merging: Resolving Interference When Merging Models NeurIPS 2023 From Mimicking to Integrating: Knowledge Integration for Pre-Trained Language Models EMNLP 2022 Merging Models with Fisher-Weighted Averaging NeurIPS 2022 Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time ICML 2022 Patching open-vocabulary models by interpolating weights NeurIPS 2022 Towards Data-Free Domain Generalization ACML 2022 Neural networks with late-phase weights ICLR 2021 A De Novo Divide-and-Merge Paradigm for Acoustic Model Optimization in Automatic Speech Recognition IJCAI 2020 Black-Box Adaptation of ASR for Accented Speech Interspeech 2020 A Robust Framework for Acoustic Scene Classification Interspeech 2019 Direct Neuron-Wise Fusion of Cognate Neural Networks Interspeech 2019 Heterogeneous Model Reuse via Optimizing Multiparty Multiclass Margin ICML 2019 Transfer Learning by Adaptive Merging of Multiple Models MIDL 2019 Unifying Heterogeneous Classifiers With Distillation CVPR 2019 Unifying and Merging Well-trained Deep Neural Networks for Inference Stage IJCAI 2018