Results 141 to 150 of about 124,133 (290)

Towards Adaptive Prefix Tuning for Parameter-Efficient Language Model Fine-tuning

, 2023
Fine-tuning large pre-trained language models on various downstream tasks with whole parameters is prohibitively expensive. Hence, Parameter-efficient fine-tuning has attracted attention that only optimizes a few task-specific parameters with the frozen ...
Zhang, Zhen-Ru, Tan, Chuanqi, Wang, Chengyu, Xu, Haiyang, Huang, Jun, Huang, Songfang   +5 more
core  

PRISM-Med: Parameter-Efficient Robust Interdomain Specialty Model for Medical Language Tasks

IEEE Access
Language Models (LMs) have shown remarkable potential in healthcare applications, yet their widespread adoption faces challenges in achieving consistent performance across diverse medical specialties while maintaining parameter efficiency.
Jieui Kang, Hyungon Ryu, Jaehyeong Sim
doaj   +1 more source

MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning

CoRR
Work in ...
Ting Jiang, Shaohan Huang, Shengyue Luo, Zihan Zhang, Haizhen Huang, Furu Wei, Weiwei Deng, Feng Sun 0008, Qi Zhang 0066, Deqing Wang, Fuzhen Zhuang   +10 more
openaire   +2 more sources

Blood Biomarkers and Surface‐Enhanced Raman Spectroscopy for Gout: A Comprehensive Review

Advanced Functional Materials, EarlyView.
Schematic illustrating gout disease progression from asymptomatic hyperuricemia to chronic tophaceous disease, highlighting the limitations of conventional imaging and biochemical diagnostics and the potential of engineered SERS platforms for ultrasensitive blood‐based detection of urate‐related biomarkers across disease stages, with the color gradient
Isuri Perera, Chiranjeevi Kanike, Appurva Tiwari, Hongyan Wu, Larry D. Unsworth, Ben Bin Xu, Xuehua Zhang   +6 more
wiley   +1 more source

Efficient and Private: Memorisation under differentially private parameter-efficient fine-tuning in language models

Fine-tuning large language models (LLMs) for specific tasks introduces privacy risks, as models may inadvertently memorise and leak sensitive training data.
Passerat-Palmbach, Jonathan, Ma, Olivia, Usynin, Dmitrii   +2 more
core  

SumLLaMA: Efficient Contrastive Representations and Fine-Tuned Adapters for Bug Report Summarization

IEEE Access
In software maintenance, concise summaries of bug reports are crucial, significantly enhancing developer efficiency and ultimately improving software quality and user experience. Large language models (LLMs) have become the standard method for bug report
Bangmeng Xiang, Yunna Shao
doaj   +1 more source

Exploring Sparsity for Parameter Efficient Fine Tuning Using Wavelets

CoRR
Efficiently adapting large foundation models is critical, especially with tight compute and memory budgets. Parameter-Efficient Fine-Tuning (PEFT) methods such as LoRA offer limited granularity and effectiveness in few-parameter regimes. We propose Wavelet Fine-Tuning (WaveFT), a novel PEFT method that learns highly sparse updates in the wavelet domain
Ahmet Bilican, Mustafa Akin Yilmaz, A. Murat Tekalp, R. Gökberk Cinbis   +3 more
openaire   +2 more sources

A Holistic Stabilization of the Anode in Lithium‐Sulfur Batteries Through a Ternary Alloy Fusion

Advanced Functional Materials, EarlyView.
LiTeAl anodes fabricated through a scalable thermal fusion technique holistically addresses the stability issues faced by lithium‐metal anodes in lithium–sulfur batteries. Aluminum forming a skeletal network with lithium suppresses dendrite growth and enhances energy density, while tellurium forming a robust SEI facilitates Li+‐ion flow.
Akhil Shenoy, Arumugam Manthiram
wiley   +1 more source

Phase Evolution Kinetics in Additive‐Free 19.75% Organic Photovoltaics Empowered by Solvent Vapor Annealing

Advanced Functional Materials, EarlyView.
Solvent vapor annealing enables kinetic control of additive‐free morphology in organic solar cells. Selective plasticization of acceptor forms an optimal fibrillar network, boosting efficiency to 19.06% (binary) and 19.75% (ternary), with ultrafast exciton dissociation and reduced recombination.
Jie Lv, Jieni Chen, Cenqi Yan, Patrick W. K. Fong, Jingjing Zhao, Daming Zheng, DingQin Hu, Xiaoman Ding, Xiaokang Sun, Chuanlin Gao, Guangye Zhang, Qianguang Yang, Can Zhu, Pei Cheng, Shirong Lu, Zhipeng Kan, Zhiwei Ren, Guangliu Ran, Wenkai Zhang, Hanlin Hu, Gang Li   +20 more
wiley   +1 more source

DoRA: Enhancing Parameter-Efficient Fine-Tuning with Dynamic Rank Distribution

Fine-tuning large-scale pre-trained models is inherently a resource-intensive task. While it can enhance the capabilities of the model, it also incurs substantial computational costs, posing challenges to the practical application of downstream tasks ...
Mao, Yulong, Huang, Kaiyu, Guan, Changhao, Mo, Fengran, Xu, Jinan, Bao, Ganglin   +5 more
core