model merging

Orthogonal Adaptation for Modular Customization of Diffusion Models CVPR 2024 Parameter Competition Balancing for Model Merging NeurIPS 2024 PRoLoRA: Partial Rotation Empowers More Parameter-Efficient LoRA ACL 2024 RankMean: Module-Level Importance Score for Merging Fine-tuned LLM Models ACL 2024 Representation Surgery for Multi-Task Model Merging ICML 2024 Reusing Transferable Weight Increments for Low-resource Style Generation EMNLP 2024 Scalable Data Ablation Approximations for Language Models through Modular Training and Merging EMNLP 2024 SELMA: Learning and Merging Skill-Specific Text-to-Image Experts with Auto-Generated Data NeurIPS 2024 Small Language Models Improve Giants by Rewriting Their Outputs EACL 2024 SQFT: Low-cost Model Adaptation in Low-precision Sparse Foundation Models EMNLP 2024 Task Arithmetic can Mitigate Synthetic-to-Real Gap in Automatic Speech Recognition EMNLP 2024 The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof NeurIPS 2024 Toward Data Efficient Model Merging between Different Datasets without Performance Degradation ACML 2024 Training-Free Pretrained Model Merging CVPR 2024 Transformer Fusion with Optimal Transport ICLR 2024 Twin-Merging: Dynamic Integration of Modular Expertise in Model Merging NeurIPS 2024 Unlocking the Potential of Model Merging for Low-Resource Languages EMNLP 2024 VB-LoRA: Extreme Parameter Efficient Fine-Tuning with Vector Banks NeurIPS 2024 Weak-to-Strong Search: Align Large Language Models via Searching over Small Language Models NeurIPS 2024 What the Weight?! A Unified Framework for Zero-Shot Knowledge Composition EACL 2024 XFT: Unlocking the Power of Code Instruction Tuning by Simply Merging Upcycled Mixture-of-Experts ACL 2024 ZipIt! Merging Models from Different Tasks without Training ICLR 2024 An Empirical Study of Multimodal Model Merging EMNLP 2023 Dataless Knowledge Fusion by Merging Weights of Language Models ICLR 2023 ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning NeurIPS 2023