Results 51 to 60 of about 5,833,459 (242)
Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari +5 more
wiley +1 more source
SLoRA: Federated Parameter Efficient Fine-Tuning of Language Models [PDF]
Transfer learning via fine-tuning pre-trained transformer models has gained significant success in delivering state-of-the-art results across various NLP tasks.
Babakniya, Sara +6 more
core +1 more source
Efficient Side-Tuning for Remote Sensing: A Low-Memory Fine-Tuning Framework
Fine-tuning pretrained models for remote sensing tasks often demands substantial computational resources. To reduce memory requirements and training costs, this article proposes a low-memory fine-tuning framework, called efficient side-tuning (EST), for ...
Haichen Yu +6 more
doaj +1 more source
LayerNorm: A key component in parameter-efficient fine-tuning [PDF]
Fine-tuning a pre-trained model, such as Bidirectional Encoder Representations from Transformers (BERT), has been proven to be an effective method for solving many natural language processing (NLP) tasks. However, due to the large number of parameters in
ValizadehAslani, Taha, Liang, Hualou
core +1 more source
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran +6 more
wiley +1 more source
Digitalizing electroplating requires both domain knowledge and interoperability. This work introduces PlatOn, a domain ontology for trivalent chromium plating and coating characterization, and a hybrid pipeline that aligns it to a mid‐level reference ontology by combining eight similarity metrics with language model reasoning. Expert‐validated mappings
Janik Harter +10 more
wiley +1 more source
Activation-Guided Low-Rank Parameter Adaptation for Efficient Model Fine-Tuning
Fine-tuning large language models is computationally expensive, and while existing parameter-efficient methods like Low-Rank Adaptation (LoRA) reduce computational costs, they are limited by suboptimal initialization strategies.
Qingchen Wang, Shengyu Shen
doaj +1 more source
Postbuild annealing systematically modifies the phase fractions and morphology of EB‐PBF processed Mo–9Si–8B. Quantitative microstructure–property correlations reveal how controlled phase evolution enhances high‐temperature compressive strength and creep resistance.
Christopher Schmidt +5 more
wiley +1 more source
Symbiotic Tuning: A Simple Approach for Enhancing Task Performance of Side-Tuning
Reducing computational and memory overhead in fine-tuning large language models remains a significant challenge in natural language processing. While parameter-efficient fine-tuning (PEFT) methods, such as LoRA, have gained attention for reducing ...
Zhi-Quan Feng +3 more
doaj +1 more source
Adaptive Foam 3D Printing of Ultralight and Multifunctional Materials
Adaptive foam 3D printing, enabled by expandable microspheres, imparts cellular structures to thermoplastic and thermosetting polymers, manufactured through a variety of processes including fused filament fabrication, direct ink writing, digital light processing, and inkjet printing.
Nariman Rajabifar, Amir Ameli
wiley +1 more source

