Weight Scope Alignment: A Frustratingly Easy Method for Model Merging
Fuente:
arXiv
Saved in:
| Main Authors: | Xu, Yichu, Li, Xin-Chun, Gan, Le, Zhan, De-Chuan |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Model Assembly Learning with Heterogeneous Layer Weight Merging
by: Zhang, Yi-Kai, et al.
Published: (2025)
by: Zhang, Yi-Kai, et al.
Published: (2025)
FOUNDER: Grounding Foundation Models in World Models for Open-Ended Embodied Decision Making
by: Wang, Yucen, et al.
Published: (2025)
by: Wang, Yucen, et al.
Published: (2025)
Visualizing, Rethinking, and Mining the Loss Landscape of Deep Neural Networks
by: Xu, Yichu, et al.
Published: (2024)
by: Xu, Yichu, et al.
Published: (2024)
Reward Models in Deep Reinforcement Learning: A Survey
by: Yu, Rui, et al.
Published: (2025)
by: Yu, Rui, et al.
Published: (2025)
Revisiting Weight Averaging for Model Merging
by: Choi, Jiho, et al.
Published: (2024)
by: Choi, Jiho, et al.
Published: (2024)
Exploring and Exploiting the Asymmetric Valley of Deep Neural Networks
by: Li, Xin-Chun, et al.
Published: (2024)
by: Li, Xin-Chun, et al.
Published: (2024)
Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision
by: Sun, Zhiqing, et al.
Published: (2024)
by: Sun, Zhiqing, et al.
Published: (2024)
Frustratingly Easy Feature Reconstruction for Out-of-Distribution Detection
by: Wang, Yingsheng, et al.
Published: (2025)
by: Wang, Yingsheng, et al.
Published: (2025)
NegMerge: Sign-Consensual Weight Merging for Machine Unlearning
by: Kim, Hyo Seo, et al.
Published: (2024)
by: Kim, Hyo Seo, et al.
Published: (2024)
Model Merging in the Essential Subspace
by: Li, Longhua, et al.
Published: (2026)
by: Li, Longhua, et al.
Published: (2026)
From Coefficients to Directions: Rethinking Model Merging with Directional Alignment
by: Chen, Zhikang, et al.
Published: (2025)
by: Chen, Zhikang, et al.
Published: (2025)
DIDA: Denoised Imitation Learning based on Domain Adaptation
by: Huang, Kaichen, et al.
Published: (2024)
by: Huang, Kaichen, et al.
Published: (2024)
IterIS: Iterative Inference-Solving Alignment for LoRA Merging
by: Chen, Hongxu, et al.
Published: (2024)
by: Chen, Hongxu, et al.
Published: (2024)
How to Weight Multitask Finetuning? Fast Previews via Bayesian Model-Merging
by: Maldonado, Hugo Monzón, et al.
Published: (2024)
by: Maldonado, Hugo Monzón, et al.
Published: (2024)
CAT Merging: A Training-Free Approach for Resolving Conflicts in Model Merging
by: Sun, Wenju, et al.
Published: (2025)
by: Sun, Wenju, et al.
Published: (2025)
Training-free Heterogeneous Model Merging
by: Xu, Zhengqi, et al.
Published: (2024)
by: Xu, Zhengqi, et al.
Published: (2024)
SENSOR: Imitate Third-Person Expert's Behaviors via Active Sensoring
by: Huang, Kaichen, et al.
Published: (2024)
by: Huang, Kaichen, et al.
Published: (2024)
FW-Merging: Scaling Model Merging with Frank-Wolfe Optimization
by: Chen, Hao Mark, et al.
Published: (2025)
by: Chen, Hao Mark, et al.
Published: (2025)
MIN-Merging: Merge the Important Neurons for Model Merging
by: Liang, Yunfei
Published: (2025)
by: Liang, Yunfei
Published: (2025)
MergeNet: Knowledge Migration across Heterogeneous Models, Tasks, and Modalities
by: Li, Kunxi, et al.
Published: (2024)
by: Li, Kunxi, et al.
Published: (2024)
To Compress or Not? Pushing the Frontier of Lossless GenAI Model Weights Compression with Exponent Concentration
by: Yang, Zeyu, et al.
Published: (2025)
by: Yang, Zeyu, et al.
Published: (2025)
Bayesian Model Merging
by: Li, Kaiyang, et al.
Published: (2026)
by: Li, Kaiyang, et al.
Published: (2026)
MergeMix: Optimizing Mid-Training Data Mixtures via Learnable Model Merging
by: Wang, Jiapeng, et al.
Published: (2026)
by: Wang, Jiapeng, et al.
Published: (2026)
A Novel Hierarchical Integration Method for Efficient Model Merging in Medical LLMs
by: Timilsina, Prakrit, et al.
Published: (2025)
by: Timilsina, Prakrit, et al.
Published: (2025)
The Reward Model Selection Crisis in Personalized Alignment
by: Rezk, Fady, et al.
Published: (2025)
by: Rezk, Fady, et al.
Published: (2025)
Model Merging and Safety Alignment: One Bad Model Spoils the Bunch
by: Hammoud, Hasan Abed Al Kader, et al.
Published: (2024)
by: Hammoud, Hasan Abed Al Kader, et al.
Published: (2024)
Merging Smarter, Generalizing Better: Enhancing Model Merging on OOD Data
by: Zhang, Bingjie, et al.
Published: (2025)
by: Zhang, Bingjie, et al.
Published: (2025)
Multi-Level Collaboration in Model Merging
by: Li, Qi, et al.
Published: (2025)
by: Li, Qi, et al.
Published: (2025)
Easy Adaptation: An Efficient Task-Specific Knowledge Injection Method for Large Models in Resource-Constrained Environments
by: Chen, Dong, et al.
Published: (2025)
by: Chen, Dong, et al.
Published: (2025)
PSO-Merging: Merging Models Based on Particle Swarm Optimization
by: Zhang, Kehao, et al.
Published: (2025)
by: Zhang, Kehao, et al.
Published: (2025)
Neural Thickets: Diverse Task Experts Are Dense Around Pretrained Weights
by: Gan, Yulu, et al.
Published: (2026)
by: Gan, Yulu, et al.
Published: (2026)
Decom-Renorm-Merge: Model Merging on the Right Space Improves Multitasking
by: Chaichana, Yuatyong, et al.
Published: (2025)
by: Chaichana, Yuatyong, et al.
Published: (2025)
Superpose Task-specific Features for Model Merging
by: Qiu, Haiquan, et al.
Published: (2025)
by: Qiu, Haiquan, et al.
Published: (2025)
Fine, I'll Merge It Myself: A Multi-Fidelity Framework for Automated Model Merging
by: Su, Guinan, et al.
Published: (2025)
by: Su, Guinan, et al.
Published: (2025)
Model Merging: Foundations and Algorithms
by: Crisostomi, Donato
Published: (2026)
by: Crisostomi, Donato
Published: (2026)
Navigating the Alignment-Calibration Trade-off: A Pareto-Superior Frontier via Model Merging
by: Hu, Tiancheng, et al.
Published: (2025)
by: Hu, Tiancheng, et al.
Published: (2025)
MergeDNA: Context-aware Genome Modeling with Dynamic Tokenization through Token Merging
by: Li, Siyuan, et al.
Published: (2025)
by: Li, Siyuan, et al.
Published: (2025)
BD-Merging: Bias-Aware Dynamic Model Merging with Evidence-Guided Contrastive Learning
by: Xie, Yuhan, et al.
Published: (2026)
by: Xie, Yuhan, et al.
Published: (2026)
Alignment through Meta-Weighted Online Sampling: Bridging the Gap between Data Generation and Preference Optimization
by: Yang, Junming, et al.
Published: (2025)
by: Yang, Junming, et al.
Published: (2025)
Sparsity-Aware Evolution for Model Merging
by: Zhang, Huan, et al.
Published: (2026)
by: Zhang, Huan, et al.
Published: (2026)
Similar Items
-
Model Assembly Learning with Heterogeneous Layer Weight Merging
by: Zhang, Yi-Kai, et al.
Published: (2025) -
FOUNDER: Grounding Foundation Models in World Models for Open-Ended Embodied Decision Making
by: Wang, Yucen, et al.
Published: (2025) -
Visualizing, Rethinking, and Mining the Loss Landscape of Deep Neural Networks
by: Xu, Yichu, et al.
Published: (2024) -
Reward Models in Deep Reinforcement Learning: A Survey
by: Yu, Rui, et al.
Published: (2025) -
Revisiting Weight Averaging for Model Merging
by: Choi, Jiho, et al.
Published: (2024)