Imagen de Portada

Personalized Collaborative Fine-Tuning for On-Device Large Language Models

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Wagner, Nicolas, Fan, Dongyang, Jaggi, Martin
Formato:	Preprint
Publicado:	2024
Materias:	Computation and Language Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

On-Device Collaborative Language Modeling via a Mixture of Generalists and Specialists
por: Fan, Dongyang, et al.
Publicado: (2024)

Towards an empirical understanding of MoE design choices
por: Fan, Dongyang, et al.
Publicado: (2024)

Beyond URLs: Metadata Diversity and Position for Efficient LLM Pretraining
por: Fan, Dongyang, et al.
Publicado: (2025)

PocketLLM: Enabling On-Device Fine-Tuning for Personalized LLMs
por: Peng, Dan, et al.
Publicado: (2024)

Less but Better: Parameter-Efficient Fine-Tuning of Large Language Models for Personality Detection
por: Shen, Lingzhi, et al.
Publicado: (2025)

Dissecting Fine-Tuning Unlearning in Large Language Models
por: Hong, Yihuai, et al.
Publicado: (2024)

How Multilingual Are Large Language Models Fine-Tuned for Translation?
por: Richburg, Aquia, et al.
Publicado: (2024)

Can Performant LLMs Be Ethical? Quantifying the Impact of Web Crawling Opt-Outs
por: Fan, Dongyang, et al.
Publicado: (2025)

Fine-Tuning Large Language Models to Appropriately Abstain with Semantic Entropy
por: Tjandra, Benedict Aaron, et al.
Publicado: (2024)

Communication-Efficient and Tensorized Federated Fine-Tuning of Large Language Models
por: Ghiasvand, Sajjad, et al.
Publicado: (2024)

SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models
por: Lu, Xudong, et al.
Publicado: (2024)

Scaling Sparse Fine-Tuning to Large Language Models
por: Ansell, Alan, et al.
Publicado: (2024)

Boosting Large Language Models with Mask Fine-Tuning
por: Zhang, Mingyuan, et al.
Publicado: (2025)

Enhancing Multilingual LLM Pretraining with Model-Based Data Selection
por: Messmer, Bettina, et al.
Publicado: (2025)

Hyperbolic Fine-Tuning for Large Language Models
por: Yang, Menglin, et al.
Publicado: (2024)

TPP-LLM: Modeling Temporal Point Processes by Efficiently Fine-Tuning Large Language Models
por: Liu, Zefang, et al.
Publicado: (2024)

Empirical Analysis of Efficient Fine-Tuning Methods for Large Pre-Trained Language Models
por: Doering, Nigel, et al.
Publicado: (2024)

DropBP: Accelerating Fine-Tuning of Large Language Models by Dropping Backward Propagation
por: Woo, Sunghyeon, et al.
Publicado: (2024)

Fine-Tuned Large Language Models for Symptom Recognition from Spanish Clinical Text
por: Shaaban, Mai A., et al.
Publicado: (2024)

Exploring Parameter-Efficient Fine-Tuning Techniques for Code Generation with Large Language Models
por: Weyssow, Martin, et al.
Publicado: (2023)

DoGE: Domain Reweighting with Generalization Estimation
por: Fan, Simin, et al.
Publicado: (2023)

Crafting Efficient Fine-Tuning Strategies for Large Language Models
por: Oliver, Michael, et al.
Publicado: (2024)

Improving Large Language Models with Concept-Aware Fine-Tuning
por: Chen, Michael K., et al.
Publicado: (2025)

Memory-Efficient Structured Backpropagation for On-Device LLM Fine-Tuning
por: Park, Juneyoung, et al.
Publicado: (2026)

Fine-Tuning Language Models with Just Forward Passes
por: Malladi, Sadhika, et al.
Publicado: (2023)

Reinforcement Learning without Human Feedback for Last Mile Fine-Tuning of Large Language Models
por: Solway, Alec
Publicado: (2024)

L4Q: Parameter Efficient Quantization-Aware Fine-Tuning on Large Language Models
por: Jeon, Hyesung, et al.
Publicado: (2024)

Simultaneous Computation and Memory Efficient Zeroth-Order Optimizer for Fine-Tuning Large Language Models
por: Wang, Fei, et al.
Publicado: (2024)

Federated Fine-Tuning of Large Language Models: Kahneman-Tversky vs. Direct Preference Optimization
por: Spadea, Fernando, et al.
Publicado: (2025)

Synthetic Data Generation in Low-Resource Settings via Fine-Tuning of Large Language Models
por: Kaddour, Jean, et al.
Publicado: (2023)

On-Device Fine-Tuning via Backprop-Free Zeroth-Order Optimization
por: Katti, Prabodh, et al.
Publicado: (2025)

Enhancing BERT Fine-Tuning for Sentiment Analysis in Lower-Resourced Languages
por: Kubík, Jozef, et al.
Publicado: (2025)

Enhancing Event Reasoning in Large Language Models through Instruction Fine-Tuning with Semantic Causal Graphs
por: Bethany, Mazal, et al.
Publicado: (2024)

Dynamic Adaptation of LoRA Fine-Tuning for Efficient and Task-Specific Optimization of Large Language Models
por: Liao, Xiaoxuan, et al.
Publicado: (2025)

CoTFormer: A Chain-of-Thought Driven Architecture with Budget-Adaptive Computation Cost at Inference
por: Mohtashami, Amirkeivan, et al.
Publicado: (2023)

Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models
por: Chow, Yinlam, et al.
Publicado: (2024)

Enhancing Trust in Large Language Models via Uncertainty-Calibrated Fine-Tuning
por: Krishnan, Ranganath, et al.
Publicado: (2024)

Fine-Tuning Discrete Diffusion Models with Policy Gradient Methods
por: Zekri, Oussama, et al.
Publicado: (2025)

Comparative Analysis of Different Efficient Fine Tuning Methods of Large Language Models (LLMs) in Low-Resource Setting
por: Srinivasan, Krishna Prasad Varadarajan, et al.
Publicado: (2024)

LoRA-SP: Streamlined Partial Parameter Adaptation for Resource-Efficient Fine-Tuning of Large Language Models
por: Wu, Yichao, et al.
Publicado: (2024)