RevFFN: Memory-Efficient Full-Parameter Fine-Tuning of Mixture-of-Experts LLMs with Reversible Blocks
Fuente:
arXiv
Saved in:
| Main Authors: | Liu, Ningyuan, Yang, Jing, Cai, Kaitong, Wang, Keze |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Backward-Friendly Optimization: Training Large Language Models with Approximate Gradients under Memory Constraints
by: Yang, Jing, et al.
Published: (2025)
by: Yang, Jing, et al.
Published: (2025)
Parameter-Efficient Fine-Tuning of LLMs with Mixture of Space Experts
by: Zhang, Buze, et al.
Published: (2026)
by: Zhang, Buze, et al.
Published: (2026)
Guardian: Decoupling Exploration from Safety in Reinforcement Learning
by: Cai, Kaitong, et al.
Published: (2025)
by: Cai, Kaitong, et al.
Published: (2025)
Learning Dynamics of VLM Finetuning
by: Zhang, Jusheng, et al.
Published: (2025)
by: Zhang, Jusheng, et al.
Published: (2025)
MAT-Agent: Adaptive Multi-Agent Training Optimization
by: Zhang, Jusheng, et al.
Published: (2025)
by: Zhang, Jusheng, et al.
Published: (2025)
PERFT: Parameter-Efficient Routed Fine-Tuning for Mixture-of-Expert Model
by: Liu, Yilun, et al.
Published: (2024)
by: Liu, Yilun, et al.
Published: (2024)
CF-VLM:CounterFactual Vision-Language Fine-tuning
by: Zhang, Jusheng, et al.
Published: (2025)
by: Zhang, Jusheng, et al.
Published: (2025)
Parameter-Efficient Routed Fine-Tuning: Mixture-of-Experts Demands Mixture of Adaptation Modules
by: Liu, Yilun, et al.
Published: (2025)
by: Liu, Yilun, et al.
Published: (2025)
UMoE: Unifying Attention and FFN with Shared Experts
by: Yang, Yuanhang, et al.
Published: (2025)
by: Yang, Yuanhang, et al.
Published: (2025)
Causal Invariance and Counterfactual Learning Driven Cooperative Game for Multi-Label Classification
by: Fan, Yijia, et al.
Published: (2025)
by: Fan, Yijia, et al.
Published: (2025)
MELINOE: Fine-Tuning Enables Memory-Efficient Inference for Mixture-of-Experts Models
by: Raje, Arian, et al.
Published: (2026)
by: Raje, Arian, et al.
Published: (2026)
TT-LoRA MoE: Unifying Parameter-Efficient Fine-Tuning and Sparse Mixture-of-Experts
by: Kunwar, Pradip, et al.
Published: (2025)
by: Kunwar, Pradip, et al.
Published: (2025)
Rational ANOVA Networks
by: Zhang, Jusheng, et al.
Published: (2026)
by: Zhang, Jusheng, et al.
Published: (2026)
Kolmogorov-Arnold Fourier Networks
by: Zhang, Jusheng, et al.
Published: (2025)
by: Zhang, Jusheng, et al.
Published: (2025)
Rank Also Matters: Hierarchical Configuration for Mixture of Adapter Experts in LLM Fine-Tuning
by: Cong, Peizhuang, et al.
Published: (2025)
by: Cong, Peizhuang, et al.
Published: (2025)
From LLMs to Edge: Parameter-Efficient Fine-Tuning on Edge Devices
by: Slamanig, Georg, et al.
Published: (2025)
by: Slamanig, Georg, et al.
Published: (2025)
Parameter-Efficient Continual Fine-Tuning: A Survey
by: Coleman, Eric Nuertey, et al.
Published: (2025)
by: Coleman, Eric Nuertey, et al.
Published: (2025)
Position-Aware Parameter Efficient Fine-Tuning Approach for Reducing Positional Bias in LLMs
by: Zhang, Zheng, et al.
Published: (2024)
by: Zhang, Zheng, et al.
Published: (2024)
Spectral Gating Networks
by: Zhang, Jusheng, et al.
Published: (2026)
by: Zhang, Jusheng, et al.
Published: (2026)
Efficiently Editing Mixture-of-Experts Models with Compressed Experts
by: He, Yifei, et al.
Published: (2025)
by: He, Yifei, et al.
Published: (2025)
A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models
by: Sun, Mengyang, et al.
Published: (2025)
by: Sun, Mengyang, et al.
Published: (2025)
A Scalable Curiosity-Driven Game-Theoretic Framework for Long-Tail Multi-Label Learning in Data Mining
by: Yang, Jing, et al.
Published: (2026)
by: Yang, Jing, et al.
Published: (2026)
Why Keep Your Doubts to Yourself? Trading Visual Uncertainties in Multi-Agent Bandit Systems
by: Zhang, Jusheng, et al.
Published: (2026)
by: Zhang, Jusheng, et al.
Published: (2026)
Parameter-Efficient Fine-Tuning in Large Models: A Survey of Methodologies
by: Wang, Luping, et al.
Published: (2024)
by: Wang, Luping, et al.
Published: (2024)
TuckA: Hierarchical Compact Tensor Experts for Efficient Fine-Tuning
by: Lei, Qifeng, et al.
Published: (2025)
by: Lei, Qifeng, et al.
Published: (2025)
Efficiency vs. Alignment: Investigating Safety and Fairness Risks in Parameter-Efficient Fine-Tuning of LLMs
by: Taraghi, Mina, et al.
Published: (2025)
by: Taraghi, Mina, et al.
Published: (2025)
Dynamic Mixture of Experts: An Auto-Tuning Approach for Efficient Transformer Models
by: Guo, Yongxin, et al.
Published: (2024)
by: Guo, Yongxin, et al.
Published: (2024)
Hallucination Detection in LLMs: Fast and Memory-Efficient Fine-Tuned Models
by: Arteaga, Gabriel Y., et al.
Published: (2024)
by: Arteaga, Gabriel Y., et al.
Published: (2024)
Long Exposure: Accelerating Parameter-Efficient Fine-Tuning for LLMs under Shadowy Sparsity
by: Wang, Tuowei, et al.
Published: (2025)
by: Wang, Tuowei, et al.
Published: (2025)
A Bayesian Hybrid Parameter-Efficient Fine-Tuning Method for Large Language Models
by: Chai, Yidong, et al.
Published: (2025)
by: Chai, Yidong, et al.
Published: (2025)
EBFT: Effective and Block-Wise Fine-Tuning for Sparse LLMs
by: Guo, Song, et al.
Published: (2024)
by: Guo, Song, et al.
Published: (2024)
Parameter Efficiency Is Not Memory Efficiency: Rethinking Fine-Tuning for On-Device LLM Adaptation
by: Tenison, Irene, et al.
Published: (2026)
by: Tenison, Irene, et al.
Published: (2026)
Upcycling Instruction Tuning from Dense to Mixture-of-Experts via Parameter Merging
by: Hui, Tingfeng, et al.
Published: (2024)
by: Hui, Tingfeng, et al.
Published: (2024)
Understanding Expert Structures on Minimax Parameter Estimation in Contaminated Mixture of Experts
by: Yan, Fanqi, et al.
Published: (2024)
by: Yan, Fanqi, et al.
Published: (2024)
Parameter-Efficient Fine-Tuning with Discrete Fourier Transform
by: Gao, Ziqi, et al.
Published: (2024)
by: Gao, Ziqi, et al.
Published: (2024)
Deconfounded Causality-aware Parameter-Efficient Fine-Tuning for Problem-Solving Improvement of LLMs
by: Wang, Ruoyu, et al.
Published: (2024)
by: Wang, Ruoyu, et al.
Published: (2024)
ESSAM: A Novel Competitive Evolution Strategies Approach to Reinforcement Learning for Memory Efficient LLMs Fine-Tuning
by: Sun, Zhishen, et al.
Published: (2026)
by: Sun, Zhishen, et al.
Published: (2026)
Parameter-Efficient Fine-Tuning for Foundation Models
by: Zhang, Dan, et al.
Published: (2025)
by: Zhang, Dan, et al.
Published: (2025)
Mixtures of Experts Unlock Parameter Scaling for Deep RL
by: Obando-Ceron, Johan, et al.
Published: (2024)
by: Obando-Ceron, Johan, et al.
Published: (2024)
PiCa: Parameter-Efficient Fine-Tuning with Column Space Projection
by: Hwang, Junseo, et al.
Published: (2025)
by: Hwang, Junseo, et al.
Published: (2025)
Similar Items
-
Backward-Friendly Optimization: Training Large Language Models with Approximate Gradients under Memory Constraints
by: Yang, Jing, et al.
Published: (2025) -
Parameter-Efficient Fine-Tuning of LLMs with Mixture of Space Experts
by: Zhang, Buze, et al.
Published: (2026) -
Guardian: Decoupling Exploration from Safety in Reinforcement Learning
by: Cai, Kaitong, et al.
Published: (2025) -
Learning Dynamics of VLM Finetuning
by: Zhang, Jusheng, et al.
Published: (2025) -
MAT-Agent: Adaptive Multi-Agent Training Optimization
by: Zhang, Jusheng, et al.
Published: (2025)