Results 111 to 120 of about 226,203 (262)

NeuroAda: Activating Each Neuron’s Potential for Parameter-Efficient Fine-Tuning

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Existing parameter-efficient fine-tuning (PEFT) methods primarily fall into two categories: addition-based and selective in-situ adaptation. The former, such as LoRA, introduce additional modules to adapt the model to downstream tasks, offering strong memory efficiency.
Zhang, Zhi, Shen, Yixian, Cao, Congfeng, Shutova, Ekaterina   +3 more
openaire   +2 more sources

Synchrotron Radiation for Quantum Technology

Advanced Functional Materials, EarlyView.
Materials and interfaces underpin quantum technologies, with synchrotron and FEL methods key to understanding and optimizing them. Advances span superconducting and semiconducting qubits, 2D materials, and topological systems, where strain, defects, and interfaces govern performance.
Oliver Rader, Sakura Pascarelli, Klaus Attenkofer, Anna A. Makarova, Karsten Holldack, Kai Rossnagel, Kristiaan Temst, George Kourousias, Stefano Carretta, Caterina Biscari, Helmut Dosch   +10 more
wiley   +1 more source

Hydra: Multi-head low-rank adaptation for parameter efficient fine-tuning

Neural Networks
The recent surge in large-scale foundation models has spurred the development of efficient methods for adapting these models to various downstream tasks. Low-rank adaptation methods, such as LoRA, have gained significant attention due to their outstanding parameter efficiency and no additional inference latency.
Sanghyeon Kim, Hyunmo Yang, Yunghyun Kim, Youngjoon Hong, Eunbyung Park   +4 more
openaire   +3 more sources

Atomic Size Misfit for Electrocatalytic Small Molecule Activation

Advanced Functional Materials, EarlyView.
This review explores the application and mechanisms of atomic size misfit in catalysis for small molecule activation, focusing on how structural defects and electronic properties can effectively lower the energy barriers of chemical bonds in molecules like H2O, CO2, and N2.
Ping Hong, Changfan Xu, Huaping Zhao, Yong Lei   +3 more
wiley   +1 more source

MPVT: An Efficient Multi-Modal Prompt Vision Tracker for Visual Target Tracking

Applied Sciences
Visual target tracking is a fundamental task in computer vision. Combining multi-modal information with tracking leverages complementary information, which improves the precision and robustness of trackers.
Jianyu Xie, Yan Fu, Junlin Zhou, Tianxiang He, Xiaopeng Wang, Yuke Fang, Duanbing Chen   +6 more
doaj   +1 more source

Parameter-Efficient Fine-Tuning with Discrete Fourier Transform

Accepted by ICML ...
Gao, Ziqi, Wang, Qichao, Chen, Aochuan, Liu, Zijing, Wu, Bingzhe, Chen, Liang, Li, Jia   +6 more
openaire   +2 more sources

Copper‐based Materials for Photo and Electrocatalytic Process: Advancing Renewable Energy and Environmental Applications

Advanced Functional Materials, EarlyView.
Cu‐based catalysts as a cornerstone in advancing sustainable energy technologies are fully reviewed in this manuscript, highlighting their potential in photo‐ and electrocatalysis. It includes metallic copper, copper oxides, copper sulfides, copper halide perovskites, copper‐based metal–organic frameworks (MOFs), and covalent organic frameworks (COFs),
Jéssica C. de Almeida, Yanjie Wang, Thais A. Rodrigues, Paulo H. H. Nunes, Vagner R. de Mendonça, Paulo H. E. Falsetti, Leticia V. Savazi, Tao He, Alexandra V. Bardakova, Aida V. Rudakova, Jie Tian, Alexei V. Emeline, Osmando F. Lopes, Antonio Otavio T. Patrocínio, Jia Hong Pan, Caue Ribeiro, Detlef W. Bahnemann   +16 more
wiley   +1 more source

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

Parameter-Efficient Subspace Optimization for LLM Fine-Tuning

This paper develops a new perspective on parameter-efficient fine-tuning for LLMs, inspired by the classical theory of subspace minimization. We introduce a unifying framework, Parameter-Efficient Subspace Optimization (PESO), which not only recovers many existing methods such as LoRA but also bridges them with the principled algorithmic and ...
Lou, Yuchen, Ye, Zeqi, Chen, Minshuo
openaire   +2 more sources

Engineering Porous Hollow Metal‐Poly(Heptazine Imide) Spheres: An Optimized Synthetic Strategy for Controlling Surface, Morphology, and Properties

Advanced Functional Materials, EarlyView.
Hollow poly(heptazine imide) spheres are prepared through a novel approach that integrates hard templating with ionothermal synthesis. This method enables precise control over surface area, pore volume, hydrophilicity, light absorption, band position, and metal composition. These tunable properties facilitate the customized design of semiconductors for
Lingli Ni, Erik Troschke, Henrik Vorwerk, Shiva Shahbazi Avarvand, Andreas Stihl, Nadzeya Brezhneva, Marius Hermesdorf, Desirée Leistenschneider, Felix H. Schacher, Jacob Schneidewind, Martin Oschatz   +10 more
wiley   +1 more source