Results 101 to 110 of about 5,833,459 (242)

Gradient‐Conductivity Architecture Enables Synchronous Enhancement of Sensitivity and Detection Range in Multifunctional All‐Paper Sensors

Advanced Functional Materials, EarlyView.
A gradient‐engineered all‐paper sensor is fabricated by integrating MXene and in situ grown AgNPs within hierarchical cellulose networks. The device breaks the sensitivity–detection range trade‐off through cascaded conductive pathways, enabling ultrahigh pressure sensitivity, humidity–pressure decoupled dual‐mode sensing, and outstanding EMI shielding,
Ao Li, Jun Xu, Dezhong Xu, Zhaohui Zhang, Jiyi Li, Daxian Cao, Kefu Chen, Mizi Fan   +7 more
wiley   +1 more source

Performance and Computational Cost of Full and Parameter-Efficient Fine Tuning for Arabic Sentiment Classification Across Training Set Sizes

Computation
Pre-trained language models are typically adapted to downstream tasks via full fine tuning. However, this entails substantial computational and memory overhead.
Teif Aldaajani, Morooj Alqurashi, Sarah Aljuaid, Maha Jarallah Althobaiti   +3 more
doaj   +1 more source

Load Distributing Metamaterials Via Discrete Optimization

Advanced Functional Materials, EarlyView.
Mechanical metamaterials are computationally optimized to homogenize transmitted forces by minimizing the spread of reaction forces. The resulting architectures transform localized loading into broader, more uniform force distributions and experimentally demonstrate robust load spreading under quasi‐static and impact loading.
Andrea Detry, Hannes Holey, Raja Zulkarnain, Roberto Guerra, Ilaria Papa, Michael Zaiser, Stefano Zapperi   +6 more
wiley   +1 more source

Enhancing Text-Based Deepfake Detection: A Comprehensive Evaluation of LoRA Fine-Tuned Large Language Models

IEEE Access
The rapid progress of large language models (LLMs) has enabled highly convincing text-based deepfakes on social media, threatening information integrity. Existing zero-shot and few-shot detection methods suffer from unstable performance, while full-model
Ammar Mohammed, Rania Kora
doaj   +1 more source

Multistage, Self‐Sensing Artificial Muscles With Coordination From Liquid Crystal Elastomer‐Graphene Composite Fibers

Advanced Functional Materials, EarlyView.
Inspired by skeletal muscles’ precision and endurance, CoilLCE integrates a self‐sensing liquid crystal elastomer/graphene artificial muscle with an embedded Joule‐heating copper coil, enabling closed‐loop multistage actuation with programmable intermediate states (strain accuracy of 2%), and antagonistic coordination (32% total strain). These features
Ziyun Zhang, Xuelin Wu, Yinding Chi, Qingya Huang, Yaoye Hong, Antonio Proctor Martinez, Jingxian Wu, Bingzhi He, Cynthia Sung, Shu Yang   +9 more
wiley   +1 more source

Med42 -- Evaluating Fine-Tuning Strategies for Medical LLMs: Full-Parameter vs. Parameter-Efficient Approaches [PDF]

This study presents a comprehensive analysis and comparison of two predominant fine-tuning methodologies - full-parameter fine-tuning and parameter-efficient tuning - within the context of medical Large Language Models (LLMs).
Al-Mahrooqi, Ahmed, Khan, Shadab, Vassilieva, Natalia, Christophe, Clément, Kanakiya, Bhargav, Chen, Charles, Salman, Muhammad Umar, Pimentel, Marco AF, Kanithi, Praveen K, Hayat, Nasir, Gosal, Gurpreet, Munjal, Prateek, Rajan, Ronnie, Amor, Boulbaba Ben, Raha, Tathagata, Gupta, Avani   +15 more
core   +1 more source

M3LoRA: Flexible Task Adaptation via Multiple Low‐Rank Matrices With Mixture‐of‐Subspaces and Minor Singular Components Initialization

CAAI Transactions on Intelligence Technology
Parameter‐efficient fine‐tuning (PEFT) has become a crucial paradigm for domain adaptation, achieving strong performance by updating only a small fraction of model parameters.
Xu Luo, Yongbin Liu, Chunping Ouyang, Ying Yu, Yang Yang   +4 more
doaj   +1 more source

Parameter-Efficient Adaptation of Qwen2.5 for Aspect-Based Sentiment Analysis Using Low-Rank Adaptation and Parameter-Efficient Fine-Tuning

Engineering Proceedings
Aspect-based sentiment analysis (ABSA) plays a vital role in deriving fine-grained sentiment from textual content. As large language models (LLMs) are increasingly adopted for automated data annotation in natural language processing (NLP), concerns have ...
Pei Ying Lim, Chuk Fong Ho, Chi Wee Tan
doaj   +1 more source

CO2‐to‐CO Conversion in a Gas‐Fed, Zero‐Gap, PEM Electrolyzer Enabled by Polycations and Nitrogen‐Doped Carbon‐Supported Cobalt Nanoparticles

Advanced Functional Materials, EarlyView.
A gas‐fed, zero‐gap, PEM CO2 electrolyzer is realized by incorporating PDDA+ ions onto the carbonaceous Co/N‐C electrocatalyst, with gaseous H2 and CO2 fed into the anode and cathode, respectively. Operating without an aqueous electrolyte, the system sustains a peak FECO of 65.1% at 100 mA cm−2. ABSTRACT Electrochemical carbon dioxide reduction (ECO2R)
Yuen Leong Chow, Hsi‐Wen Wu, Aimin Li, Yalou Guo, Duhong Chen, Jie Zhang, Paul A. Webley   +6 more
wiley   +1 more source

Small Language Models Fine-Tuning to Enable Intent-Driven Management of Kubernetes Resources

IEEE Access
Cloud-native infrastructure management increasingly demands intent-driven interfaces that translate natural language into executable commands, yet large language models (LLMs) introduce privacy risks, operational costs, and deployment constraints.
Dimitrios Brodimas, Georgios Polymanakos, Michael Birbas, Alexios Birbas   +3 more
doaj   +1 more source