LEMoE: Advanced Mixture of Experts Adaptor for Lifelong Model Editing of Large Language Models
Fuente:
arXiv
Guardado en:
| Autores principales: | Wang, Renzhi, Li, Piji |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
MEMoE: Enhancing Model Editing with Mixture of Experts Adaptors
por: Wang, Renzhi, et al.
Publicado: (2024)
por: Wang, Renzhi, et al.
Publicado: (2024)
Semantic are Beacons: A Semantic Perspective for Unveiling Parameter-Efficient Fine-Tuning in Knowledge Learning
por: Wang, Renzhi, et al.
Publicado: (2024)
por: Wang, Renzhi, et al.
Publicado: (2024)
Lifelong Knowledge Editing for Vision Language Models with Low-Rank Mixture-of-Experts
por: Chen, Qizhou, et al.
Publicado: (2024)
por: Chen, Qizhou, et al.
Publicado: (2024)
A Systematic Evaluation of Large Language Models for Natural Language Generation Tasks
por: Ni, Xuanfan, et al.
Publicado: (2024)
por: Ni, Xuanfan, et al.
Publicado: (2024)
Temporal Guidance for Large Language Models
por: Zheng, Hong-Kai, et al.
Publicado: (2026)
por: Zheng, Hong-Kai, et al.
Publicado: (2026)
Reinforced Lifelong Editing for Language Models
por: Li, Zherui, et al.
Publicado: (2025)
por: Li, Zherui, et al.
Publicado: (2025)
ELDER: Enhancing Lifelong Model Editing with Mixture-of-LoRA
por: Li, Jiaang, et al.
Publicado: (2024)
por: Li, Jiaang, et al.
Publicado: (2024)
Generating Diverse Training Samples for Relation Extraction with Large Language Models
por: Li, Zexuan, et al.
Publicado: (2025)
por: Li, Zexuan, et al.
Publicado: (2025)
EvoMoE: Expert Evolution in Mixture of Experts for Multimodal Large Language Models
por: Jing, Linglin, et al.
Publicado: (2025)
por: Jing, Linglin, et al.
Publicado: (2025)
Cluster-Driven Expert Pruning for Mixture-of-Experts Large Language Models
por: Guo, Hongcheng, et al.
Publicado: (2025)
por: Guo, Hongcheng, et al.
Publicado: (2025)
Unveiling Super Experts in Mixture-of-Experts Large Language Models
por: Su, Zunhai, et al.
Publicado: (2025)
por: Su, Zunhai, et al.
Publicado: (2025)
M-BRe: Discovering Training Samples for Relation Extraction from Unlabeled Texts with Large Language Models
por: Li, Zexuan, et al.
Publicado: (2025)
por: Li, Zexuan, et al.
Publicado: (2025)
Characteristic AI Agents via Large Language Models
por: Wang, Xi, et al.
Publicado: (2024)
por: Wang, Xi, et al.
Publicado: (2024)
5W1H Extraction With Large Language Models
por: Cao, Yang, et al.
Publicado: (2024)
por: Cao, Yang, et al.
Publicado: (2024)
Knowledge in Superposition: Unveiling the Failures of Lifelong Knowledge Editing for Large Language Models
por: Hu, Chenhui, et al.
Publicado: (2024)
por: Hu, Chenhui, et al.
Publicado: (2024)
WISE: Rethinking the Knowledge Memory for Lifelong Model Editing of Large Language Models
por: Wang, Peng, et al.
Publicado: (2024)
por: Wang, Peng, et al.
Publicado: (2024)
Bayesian Mixture of Experts For Large Language Models
por: Dialameh, Maryam, et al.
Publicado: (2025)
por: Dialameh, Maryam, et al.
Publicado: (2025)
A Survey on Mixture of Experts in Large Language Models
por: Cai, Weilin, et al.
Publicado: (2024)
por: Cai, Weilin, et al.
Publicado: (2024)
LLaVA-CMoE: Towards Continual Mixture of Experts for Large Vision-Language Models
por: Zhao, Hengyuan, et al.
Publicado: (2025)
por: Zhao, Hengyuan, et al.
Publicado: (2025)
HMoE: Heterogeneous Mixture of Experts for Language Modeling
por: Wang, An, et al.
Publicado: (2024)
por: Wang, An, et al.
Publicado: (2024)
A Closer Look into Mixture-of-Experts in Large Language Models
por: Lo, Ka Man, et al.
Publicado: (2024)
por: Lo, Ka Man, et al.
Publicado: (2024)
Upcycling Large Language Models into Mixture of Experts
por: He, Ethan, et al.
Publicado: (2024)
por: He, Ethan, et al.
Publicado: (2024)
Improving Brain-to-Image Reconstruction via Fine-Grained Text Bridging
por: Xia, Runze, et al.
Publicado: (2025)
por: Xia, Runze, et al.
Publicado: (2025)
MoE-LPR: Multilingual Extension of Large Language Models through Mixture-of-Experts with Language Priors Routing
por: Zhou, Hao, et al.
Publicado: (2024)
por: Zhou, Hao, et al.
Publicado: (2024)
HiEdit: Lifelong Model Editing with Hierarchical Reinforcement Learning
por: Wang, Yangfan, et al.
Publicado: (2026)
por: Wang, Yangfan, et al.
Publicado: (2026)
Pre-Attention Expert Prediction and Prefetching for Mixture-of-Experts Large Language Models
por: Zhu, Shien, et al.
Publicado: (2025)
por: Zhu, Shien, et al.
Publicado: (2025)
DIVE into MoE: Diversity-Enhanced Reconstruction of Large Language Models from Dense into Mixture-of-Experts
por: Feng, Yuchen, et al.
Publicado: (2025)
por: Feng, Yuchen, et al.
Publicado: (2025)
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models
por: Dai, Damai, et al.
Publicado: (2024)
por: Dai, Damai, et al.
Publicado: (2024)
Improve Language Model and Brain Alignment via Associative Memory
por: Yin, Congchi, et al.
Publicado: (2025)
por: Yin, Congchi, et al.
Publicado: (2025)
FourierMoE: Fourier Mixture-of-Experts Adaptation of Large Language Models
por: Jiang, Juyong, et al.
Publicado: (2026)
por: Jiang, Juyong, et al.
Publicado: (2026)
Not All Experts are Equal: Efficient Expert Pruning and Skipping for Mixture-of-Experts Large Language Models
por: Lu, Xudong, et al.
Publicado: (2024)
por: Lu, Xudong, et al.
Publicado: (2024)
IAA: Inner-Adaptor Architecture Empowers Frozen Large Language Model with Multimodal Capabilities
por: Wang, Bin, et al.
Publicado: (2024)
por: Wang, Bin, et al.
Publicado: (2024)
MoDES: Accelerating Mixture-of-Experts Multimodal Large Language Models via Dynamic Expert Skipping
por: Huang, Yushi, et al.
Publicado: (2025)
por: Huang, Yushi, et al.
Publicado: (2025)
SciDFM: A Large Language Model with Mixture-of-Experts for Science
por: Sun, Liangtai, et al.
Publicado: (2024)
por: Sun, Liangtai, et al.
Publicado: (2024)
OLMoE: Open Mixture-of-Experts Language Models
por: Muennighoff, Niklas, et al.
Publicado: (2024)
por: Muennighoff, Niklas, et al.
Publicado: (2024)
Mixture of Heterogeneous Grouped Experts for Language Modeling
por: Ma, Zhicheng, et al.
Publicado: (2026)
por: Ma, Zhicheng, et al.
Publicado: (2026)
When Are Experts Misrouted? Counterfactual Routing Analysis in Mixture-of-Experts Language Models
por: Yoon, Youngsik, et al.
Publicado: (2026)
por: Yoon, Youngsik, et al.
Publicado: (2026)
On the Robustness of Editing Large Language Models
por: Ma, Xinbei, et al.
Publicado: (2024)
por: Ma, Xinbei, et al.
Publicado: (2024)
DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding
por: Wu, Zhiyu, et al.
Publicado: (2024)
por: Wu, Zhiyu, et al.
Publicado: (2024)
LIBMoE: A Library for comprehensive benchmarking Mixture of Experts in Large Language Models
por: Nguyen, Nam V., et al.
Publicado: (2024)
por: Nguyen, Nam V., et al.
Publicado: (2024)
Ejemplares similares
-
MEMoE: Enhancing Model Editing with Mixture of Experts Adaptors
por: Wang, Renzhi, et al.
Publicado: (2024) -
Semantic are Beacons: A Semantic Perspective for Unveiling Parameter-Efficient Fine-Tuning in Knowledge Learning
por: Wang, Renzhi, et al.
Publicado: (2024) -
Lifelong Knowledge Editing for Vision Language Models with Low-Rank Mixture-of-Experts
por: Chen, Qizhou, et al.
Publicado: (2024) -
A Systematic Evaluation of Large Language Models for Natural Language Generation Tasks
por: Ni, Xuanfan, et al.
Publicado: (2024) -
Temporal Guidance for Large Language Models
por: Zheng, Hong-Kai, et al.
Publicado: (2026)