Image de couverture de livre

MOMA: Masked Orthogonal Matrix Alignment for Zero-Additional-Parameter Model Merging

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Kong, Fanshuang, Zhang, Richong, Nie, Zhijie, Zhou, Hang, Wang, Ziqiao, Sun, Qiang, Hu, Chunming
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Activated Parameter Locating via Causal Intervention for Model Merging
par: Kong, Fanshuang, et autres
Publié: (2024)

LH-Mix: Local Hierarchy Correlation Guided Mixup over Hierarchical Prompt Tuning
par: Kong, Fanshuang, et autres
Publié: (2024)

inversedMixup: Data Augmentation via Inverting Mixed Embeddings
par: Kong, Fanshuang, et autres
Publié: (2026)

On SkipGram Word Embedding Models with Negative Sampling: Unified Framework and Impact of Noise Distributions
par: Liu, Dezhi, et autres
Publié: (2020)

Improving Zero-Shot Cross-Lingual Transfer via Progressive Code-Switching
par: Li, Zhuoran, et autres
Publié: (2024)

Nora: Normalized Orthogonal Row Alignment for Scalable Matrix Optimizer
par: Yuan, Jinghui, et autres
Publié: (2026)

Implicit Word Reordering with Knowledge Distillation for Cross-Lingual Dependency Parsing
par: Li, Zhuoran, et autres
Publié: (2025)

Orthogonal Model Merging
par: Yang, Sihan, et autres
Publié: (2026)

Improved Operator Learning by Orthogonal Attention
par: Xiao, Zipeng, et autres
Publié: (2023)

Safety Alignment as Continual Learning: Mitigating the Alignment Tax via Orthogonal Gradient Projection
par: Sun, Guanglong, et autres
Publié: (2026)

Unraveling LoRA Interference: Orthogonal Subspaces for Robust Model Merging
par: Zhang, Haobo, et autres
Publié: (2025)

Expert Merging: Model Merging with Unsupervised Expert Alignment and Importance-Guided Layer Chunking
par: Zhang, Dengming, et autres
Publié: (2025)

Model Breadcrumbs: Scaling Multi-Task Model Merging with Sparse Masks
par: Davari, MohammadReza, et autres
Publié: (2023)

Rethinking Graph Masked Autoencoders through Alignment and Uniformity
par: Wang, Liang, et autres
Publié: (2024)

FedMerge: Federated Personalization via Model Merging
par: Chen, Shutong, et autres
Publié: (2025)

Fisher Mask Nodes for Language Model Merging
par: K, Thennal D, et autres
Publié: (2024)

From Coefficients to Directions: Rethinking Model Merging with Directional Alignment
par: Chen, Zhikang, et autres
Publié: (2025)

Non-Uniform Parameter-Wise Model Merging
par: Camacho, Albert Manuel Orozco, et autres
Publié: (2024)

Merging by Matching Models in Task Parameter Subspaces
par: Tam, Derek, et autres
Publié: (2023)

FedMuon: Accelerating Federated Learning with Matrix Orthogonalization
par: Liu, Junkang, et autres
Publié: (2025)

Decouple and Orthogonalize: A Data-Free Framework for LoRA Merging
par: Zheng, Shenghe, et autres
Publié: (2025)

Improving General Text Embedding Model: Tackling Task Conflict and Data Imbalance through Model Merging
par: Li, Mingxin, et autres
Publié: (2024)

Orthogonalized Multimodal Contrastive Learning with Asymmetric Masking for Structured Representations
par: Cissee, Carolin, et autres
Publié: (2026)

Cross-attention Secretly Performs Orthogonal Alignment in Recommendation Models
par: Lee, Hyunin, et autres
Publié: (2025)

Extra-Merge: Tracing the Rank-1 Subspace of Model Merging in Language Model Pre-Training
par: Zhou, Wenjie, et autres
Publié: (2026)

Sparse Orthogonal Parameters Tuning for Continual Learning
par: Ning, Kun-Peng, et autres
Publié: (2024)

MaskGCT: Zero-Shot Text-to-Speech with Masked Generative Codec Transformer
par: Wang, Yuancheng, et autres
Publié: (2024)

SeMe: Training-Free Language Model Merging via Semantic Alignment
par: Gu, Jian, et autres
Publié: (2025)

MergeSFL: Split Federated Learning with Feature Merging and Batch Size Regulation
par: Liao, Yunming, et autres
Publié: (2023)

Modular Delta Merging with Orthogonal Constraints: A Scalable Framework for Continual and Reversible Model Composition
par: Khan, Haris, et autres
Publié: (2025)

FedSKD: Aggregation-free Model-heterogeneous Federated Learning via Multi-dimensional Similarity Knowledge Distillation for Medical Image Classification
par: Weng, Ziqiao, et autres
Publié: (2025)

Dynamic Task Vector Grouping for Efficient Multi-Task Prompt Tuning
par: Zhang, Pieyi, et autres
Publié: (2025)

Parameter Competition Balancing for Model Merging
par: Du, Guodong, et autres
Publié: (2024)

Online Merging Optimizers for Boosting Rewards and Mitigating Tax in Alignment
par: Lu, Keming, et autres
Publié: (2024)

Adaptive Tokenization: On the Hop-Overpriority Problem in Tokenized Graph Learning Models
par: Wang, Zhibiao, et autres
Publié: (2025)

Training-Free Self-Correction for Multimodal Masked Diffusion Models
par: Ouyang, Yidong, et autres
Publié: (2026)

COMPOT: Calibration-Optimized Matrix Procrustes Orthogonalization for Transformers Compression
par: Makhov, Denis, et autres
Publié: (2026)

T3: Test-Time Model Merging in VLMs for Zero-Shot Medical Imaging Analysis
par: Imam, Raza, et autres
Publié: (2025)

Rethinking Inter-LoRA Orthogonality in Adapter Merging: Insights from Orthogonal Monte Carlo Dropout
par: Zhang, Andi, et autres
Publié: (2025)

MergeBench: A Benchmark for Merging Domain-Specialized LLMs
par: He, Yifei, et autres
Publié: (2025)