Cover Image

Data Efficient Adaptation in Large Language Models via Continuous Low-Rank Fine-Tuning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Han, Xiao, Zhao, Zimo, Wang, Wanyu, Wang, Maolin, Liu, Zitao, Chang, Yi, Zhao, Xiangyu
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

MetaLoRA: Tensor-Enhanced Adaptive Low-Rank Fine-tuning
by: Wang, Maolin, et al.
Published: (2025)

Curriculum Learning for Efficient Chain-of-Thought Distillation via Structure-Aware Masking and GRPO
by: Yu, Bowen, et al.
Published: (2026)

SIGMA: Selective Gated Mamba for Sequential Recommendation
by: Liu, Ziwei, et al.
Published: (2024)

RoSA: Enhancing Parameter-Efficient Fine-Tuning via RoPE-aware Selective Adaptation in Large Language Models
by: Pan, Dayan, et al.
Published: (2025)

Computational Limits of Low-Rank Adaptation (LoRA) Fine-Tuning for Transformer Models
by: Hu, Jerry Yao-Chieh, et al.
Published: (2024)

MSPLoRA: A Multi-Scale Pyramid Low-Rank Adaptation for Efficient Model Fine-Tuning
by: Zhao, Jiancheng, et al.
Published: (2025)

Cumulative Distribution Function based General Temporal Point Processes
by: Wang, Maolin, et al.
Published: (2024)

Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models
by: Zhang, Longteng, et al.
Published: (2026)

ShareLoRA: Parameter Efficient and Robust Large Language Model Fine-tuning via Shared Low-Rank Adaptation
by: Song, Yurun, et al.
Published: (2024)

Pre-train, Align, and Disentangle: Empowering Sequential Recommendation with Large Language Models
by: Wang, Yuhao, et al.
Published: (2024)

Contextual Attention Modulation: Towards Efficient Multi-Task Adaptation in Large Language Models
by: Pan, Dayan, et al.
Published: (2025)

GLINT-RU: Gated Lightweight Intelligent Recurrent Units for Sequential Recommender Systems
by: Zhang, Sheng, et al.
Published: (2024)

AFLoRA: Adaptive Freezing of Low Rank Adaptation in Parameter Efficient Fine-Tuning of Large Models
by: Liu, Zeyu, et al.
Published: (2024)

PrivTune: Efficient and Privacy-Preserving Fine-Tuning of Large Language Models via Device-Cloud Collaboration
by: Liu, Yi, et al.
Published: (2025)

Empowering Denoising Sequential Recommendation with Large Language Model Embeddings
by: Wu, Tongzhou, et al.
Published: (2025)

Large Multimodal Model Compression via Efficient Pruning and Distillation at AntGroup
by: Wang, Maolin, et al.
Published: (2023)

Efficient Inference Using Large Language Models with Limited Human Data: Fine-Tuning then Rectification
by: Wang, Lei, et al.
Published: (2025)

LoR2C : Low-Rank Residual Connection Adaptation for Parameter-Efficient Fine-Tuning
by: Zhao, Jiancheng, et al.
Published: (2025)

TriAdaptLoRA: Brain-Inspired Triangular Adaptive Low-Rank Adaptation for Parameter-Efficient Fine-Tuning
by: Liang, Yao, et al.
Published: (2025)

Multi-Level Safety Continual Projection for Fine-Tuned Large Language Models without Retraining
by: Han, Bing, et al.
Published: (2025)

DANCE: Resource-Efficient Neural Architecture Search with Data-Aware and Continuous Adaptation
by: Wang, Maolin, et al.
Published: (2025)

BIPEFT: Budget-Guided Iterative Search for Parameter Efficient Fine-Tuning of Large Pretrained Language Models
by: Chang, Aofei, et al.
Published: (2024)

ElaLoRA: Elastic & Learnable Low-Rank Adaptation for Efficient Model Fine-Tuning
by: Chang, Huandong, et al.
Published: (2025)

TsqLoRA: Towards Sensitivity and Quality Low-Rank Adaptation for Efficient Fine-Tuning
by: Chen, Yu, et al.
Published: (2025)

RoRA: Efficient Fine-Tuning of LLM with Reliability Optimization for Rank Adaptation
by: Liu, Jun, et al.
Published: (2025)

Matrix-Transformation Based Low-Rank Adaptation (MTLoRA): A Brain-Inspired Method for Parameter-Efficient Fine-Tuning
by: Liang, Yao, et al.
Published: (2024)

AILoRA: Function-Aware Asymmetric Initialization for Low-Rank Adaptation of Large Language Models
by: Ji, Xiaoshuang, et al.
Published: (2025)

Improving Anomalous Sound Detection via Low-Rank Adaptation Fine-Tuning of Pre-Trained Audio Models
by: Zheng, Xinhu, et al.
Published: (2024)

Controlled Low-Rank Adaptation with Subspace Regularization for Continued Training on Large Language Models
by: Lu, Yuheng, et al.
Published: (2024)

BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models
by: Wang, Yibin, et al.
Published: (2024)

Empowering Large Language Model for Sequential Recommendation via Multimodal Embeddings and Semantic IDs
by: Wang, Yuhao, et al.
Published: (2025)

LoRETTA: Low-Rank Economic Tensor-Train Adaptation for Ultra-Low-Parameter Fine-Tuning of Large Language Models
by: Yang, Yifan, et al.
Published: (2024)

GraLoRA: Granular Low-Rank Adaptation for Parameter-Efficient Fine-Tuning
by: Jung, Yeonjoon, et al.
Published: (2025)

Continual Gradient Low-Rank Projection Fine-Tuning for LLMs
by: Wang, Chenxu, et al.
Published: (2025)

RankAdaptor: Hierarchical Rank Allocation for Efficient Fine-Tuning Pruned LLMs via Performance Model
by: Zhou, Changhai, et al.
Published: (2024)

CoRA: Optimizing Low-Rank Adaptation with Common Subspace of Large Language Models
by: Xiao, Xiaojun, et al.
Published: (2024)

CTR-LoRA: Curvature-Aware and Trust-Region Guided Low-Rank Adaptation for Large Language Models
by: Wang, Zhuxuanzi, et al.
Published: (2025)

Memory-Efficient Fine-Tuning via Low-Rank Activation Compression
by: Shi, Jiang-Xin, et al.
Published: (2025)

Efficient Low Rank Attention for Long-Context Inference in Large Language Models
by: Li, Tenghui, et al.
Published: (2025)

Ravan: Multi-Head Low-Rank Adaptation for Federated Fine-Tuning
by: Raje, Arian, et al.
Published: (2025)