Results 71 to 80 of about 227,550 (285)
Activation-Guided Low-Rank Parameter Adaptation for Efficient Model Fine-Tuning
IEEE AccessFine-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
Parameter-Efficient Continual Fine-Tuning: A Survey
The emergence of large pre-trained networks has revolutionized the AI field, unlocking new possibilities and achieving unprecedented performance. However, these models inherit a fundamental limitation from traditional Machine Learning approaches: their strong dependence on the \textit{i.i.d.} assumption hinders their adaptability to dynamic learning ...
Coleman, Eric Nuertey +6 more
openaire +2 more sources
Gradient Inversion Attacks on Parameter-Efficient Fine-Tuning
2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2025)
Sami, Hasin Us +4 more
openaire +2 more sources
What Do Large Language Models Know About Materials?
Advanced Engineering Materials, EarlyView.If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
Swin-TUNA: A Novel PEFT Approach for Accurate Food Image Segmentation
IEEE AccessIn food image processing, parameter-efficient semantic segmentation is important for high-performance applications under constrained training resources.
Haotian Chen, Zhiyong Xiao
doaj +1 more source
Quantum-PEFT: Ultra parameter-efficient fine-tuning
ICLR ...
Koike-Akino, Toshiaki +5 more
openaire +2 more sources
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
Advanced Engineering Materials, EarlyView.This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice +2 more
wiley +1 more source
The Status of Neutralino Dark Matter
, 2013 The lightest neutralino in supersymmetry is the most studied dark matter candidate. This writeup reviews the status of neutralino dark matter in minimal and nonminimal supersymmetric models in light of recent null results at the XENON100 experiment and ...
Shakya, Bibhushan
core +1 more source
Elinvar Materials: Recent Progress and Challenges
Advanced Engineering Materials, EarlyView.Elinvar materials, exhibiting temperature‐invariant elastic modulus, are critical for precision instruments and emerging technologies. This article reviews recent progress in the field, with a focus on the anomalous thermoelastic behavior observed in key material systems.
Wenjie Li, Yang Ren
wiley +1 more source
Symbiotic Tuning: A Simple Approach for Enhancing Task Performance of Side-Tuning
IEEE AccessReducing 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