Saved in:
| Main Authors: | Xu, Jing, Li, Jiazheng, Zhang, Jingzhao |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2502.12706 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Rethinking Layer-wise Model Merging through Chain of Merges
by: Buzzega, Pietro, et al.
Published: (2025)
by: Buzzega, Pietro, et al.
Published: (2025)
Data Mixing Can Induce Phase Transitions in Knowledge Acquisition
by: Gu, Xinran, et al.
Published: (2025)
by: Gu, Xinran, et al.
Published: (2025)
Random Masking Finds Winning Tickets for Parameter Efficient Fine-tuning
by: Xu, Jing, et al.
Published: (2024)
by: Xu, Jing, et al.
Published: (2024)
DLink: Distilling Layer-wise and Dominant Knowledge from EEG Foundation Models
by: Wang, Jingyuan, et al.
Published: (2026)
by: Wang, Jingyuan, et al.
Published: (2026)
On Finding Small Hyper-Gradients in Bilevel Optimization: Hardness Results and Improved Analysis
by: Chen, Lesi, et al.
Published: (2023)
by: Chen, Lesi, et al.
Published: (2023)
Understanding Nonlinear Implicit Bias via Region Counts in Input Space
by: Li, Jingwei, et al.
Published: (2025)
by: Li, Jingwei, et al.
Published: (2025)
Functionally Constrained Algorithm Solves Convex Simple Bilevel Problems
by: Zhang, Huaqing, et al.
Published: (2024)
by: Zhang, Huaqing, et al.
Published: (2024)
Iterative Layer-wise Distillation for Efficient Compression of Large Language Models
by: Kovalev, Grigory, et al.
Published: (2025)
by: Kovalev, Grigory, et al.
Published: (2025)
Towards Minimizing Feature Drift in Model Merging: Layer-wise Task Vector Fusion for Adaptive Knowledge Integration
by: Sun, Wenju, et al.
Published: (2025)
by: Sun, Wenju, et al.
Published: (2025)
LARV: Data-Free Layer-wise Adaptive Rescaling Veneer for Model Merging
by: Wang, Xinyu, et al.
Published: (2026)
by: Wang, Xinyu, et al.
Published: (2026)
Improving Knowledge Distillation in Transfer Learning with Layer-wise Learning Rates
by: Kokane, Shirley, et al.
Published: (2024)
by: Kokane, Shirley, et al.
Published: (2024)
Stochastic Layer-wise Learning: Scalable and Efficient Alternative to Backpropagation
by: Yin, Bojian, et al.
Published: (2025)
by: Yin, Bojian, et al.
Published: (2025)
Towards Black-Box Membership Inference Attack for Diffusion Models
by: Li, Jingwei, et al.
Published: (2024)
by: Li, Jingwei, et al.
Published: (2024)
Capacity-Aware Mixture Law Enables Efficient LLM Data Optimization
by: Li, Jingwei, et al.
Published: (2026)
by: Li, Jingwei, et al.
Published: (2026)
Resource-Efficient Federated Multimodal Learning via Layer-wise and Progressive Training
by: Tun, Ye Lin, et al.
Published: (2024)
by: Tun, Ye Lin, et al.
Published: (2024)
Fast and Multiphase Rates for Nearest Neighbor Classifiers
by: Yang, Pengkun, et al.
Published: (2023)
by: Yang, Pengkun, et al.
Published: (2023)
Merging Models on the Fly Without Retraining: A Sequential Approach to Scalable Continual Model Merging
by: Tang, Anke, et al.
Published: (2025)
by: Tang, Anke, et al.
Published: (2025)
Geometric Layer-wise Approximation Rates for Deep Networks
by: Zhang, Shijun, et al.
Published: (2026)
by: Zhang, Shijun, et al.
Published: (2026)
FedMerge: Federated Personalization via Model Merging
by: Chen, Shutong, et al.
Published: (2025)
by: Chen, Shutong, et al.
Published: (2025)
Research and Implementation of Data Enhancement Techniques for Graph Neural Networks
by: Gu, Jingzhao, et al.
Published: (2024)
by: Gu, Jingzhao, et al.
Published: (2024)
Expert Merging: Model Merging with Unsupervised Expert Alignment and Importance-Guided Layer Chunking
by: Zhang, Dengming, et al.
Published: (2025)
by: Zhang, Dengming, et al.
Published: (2025)
On the Condition Number Dependency in Bilevel Optimization
by: Chen, Lesi, et al.
Published: (2025)
by: Chen, Lesi, et al.
Published: (2025)
Model Assembly Learning with Heterogeneous Layer Weight Merging
by: Zhang, Yi-Kai, et al.
Published: (2025)
by: Zhang, Yi-Kai, et al.
Published: (2025)
Layer-wise dynamic rank for compressing large language models
by: Mi, Zhendong, et al.
Published: (2025)
by: Mi, Zhendong, et al.
Published: (2025)
Multiplex Thinking: Reasoning via Token-wise Branch-and-Merge
by: Tang, Yao, et al.
Published: (2026)
by: Tang, Yao, et al.
Published: (2026)
LoaQ: Layer-wise Output Approximation Quantization
by: Lin, Li, et al.
Published: (2025)
by: Lin, Li, et al.
Published: (2025)
Merge-of-Thought Distillation
by: Shen, Zhanming, et al.
Published: (2025)
by: Shen, Zhanming, et al.
Published: (2025)
Layer-wise Linear Mode Connectivity
by: Adilova, Linara, et al.
Published: (2023)
by: Adilova, Linara, et al.
Published: (2023)
Layer-wise Derivative Controlled Networks
by: Martnishn, Rowan, et al.
Published: (2026)
by: Martnishn, Rowan, et al.
Published: (2026)
Model Merging via Multi-Teacher Knowledge Distillation
by: Dalili, Seyed Arshan, et al.
Published: (2025)
by: Dalili, Seyed Arshan, et al.
Published: (2025)
MergeQuant: Accurate 4-bit Static Quantization of Large Language Models by Channel-wise Calibration
by: Wang, Jinguang, et al.
Published: (2025)
by: Wang, Jinguang, et al.
Published: (2025)
SliceGX: Layer-wise GNN Explanation with Model-slicing
by: Zhu, Tingting, et al.
Published: (2025)
by: Zhu, Tingting, et al.
Published: (2025)
Determining Layer-wise Sparsity for Large Language Models Through a Theoretical Perspective
by: Huang, Weizhong, et al.
Published: (2025)
by: Huang, Weizhong, et al.
Published: (2025)
Layer-wise Weight Selection for Power-Efficient Neural Network Acceleration
by: Fang, Jiaxun, et al.
Published: (2025)
by: Fang, Jiaxun, et al.
Published: (2025)
Collaborative Adaptive Curriculum for Progressive Knowledge Distillation
by: Liu, Jing, et al.
Published: (2026)
by: Liu, Jing, et al.
Published: (2026)
Instance-Aware Graph Prompt Learning
by: Li, Jiazheng, et al.
Published: (2024)
by: Li, Jiazheng, et al.
Published: (2024)
Efficient Sampling on Riemannian Manifolds via Langevin MCMC
by: Cheng, Xiang, et al.
Published: (2024)
by: Cheng, Xiang, et al.
Published: (2024)
BARD: Bridging AutoRegressive and Diffusion Vision-Language Models Via Highly Efficient Progressive Block Merging and Stage-Wise Distillation
by: Chen, Baoyou, et al.
Published: (2026)
by: Chen, Baoyou, et al.
Published: (2026)
Merge and Guide: Unifying Model Merging and Guided Decoding for Controllable Multi-Objective Generation
by: Xie, Guofu, et al.
Published: (2025)
by: Xie, Guofu, et al.
Published: (2025)
Unifying Block-wise PTQ and Distillation-based QAT for Progressive Quantization toward 2-bit Instruction-Tuned LLMs
by: Lee, Jung Hyun, et al.
Published: (2025)
by: Lee, Jung Hyun, et al.
Published: (2025)
Similar Items
-
Rethinking Layer-wise Model Merging through Chain of Merges
by: Buzzega, Pietro, et al.
Published: (2025) -
Data Mixing Can Induce Phase Transitions in Knowledge Acquisition
by: Gu, Xinran, et al.
Published: (2025) -
Random Masking Finds Winning Tickets for Parameter Efficient Fine-tuning
by: Xu, Jing, et al.
Published: (2024) -
DLink: Distilling Layer-wise and Dominant Knowledge from EEG Foundation Models
by: Wang, Jingyuan, et al.
Published: (2026) -
On Finding Small Hyper-Gradients in Bilevel Optimization: Hardness Results and Improved Analysis
by: Chen, Lesi, et al.
Published: (2023)