One Size Does Not Fit All: Distribution-Guided Tensor-Wise Adaptive Sparsification for Model Merging
cs.CL, cs.AI, cs.LG
Submitted: 2025-08-08
Updated: 2026-10-13
Comments: Under review
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Efficient Prompting Methods for Large Language Models: A Survey
- LEWIS (LayEr WIse Sparsity) -- A Training Free Guided Model Merging Approach
- DELLA-Merging: Reducing Interference in Model Merging through Magnitude-Based Sampling
- Big Transfer (BiT): General Visual Representation Learning
- AdaRank: Adaptive Rank Pruning for Enhanced Model Merging
- GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
- A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference
- Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
- Foundations of Large Language Models
- Scalable Model Merging with Progressive Layer-wise Distillation
- Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities
- CABS: Conflict-Aware and Balanced Sparsification for Enhancing Model Merging
- Merging Smarter, Generalizing Better: Enhancing Model Merging on OOD Data
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