Results 131 to 140 of about 5,833,459 (242)

An Adaptive Inhibitory WSe2 Transistor for Retinomorphic In‐Sensor Image Processing

Advanced Functional Materials, EarlyView.
Conventional retinomorphic devices typically require deliberate gate‐bias tuning for each illumination condition. In this paper, we demonstrate an adaptive inhibitory WSe2 transistor that uses photo‐induced regime shift between the subthreshold and accumulation modes to achieve decision‐free, intensity‐adaptive image processing within a single pixel ...
Juhwan Baek, Junhwa Oh, Hyeonjung Kim, Minsik Park, Haein Cho, Jin Young Park, Hyeonchang Son, Taeyun Kim, Sung‐Un An, Yamin Zhang, Hyeon‐Jin Shin, Seyong Oh, Dong‐Ho Kang   +12 more
wiley   +1 more source

GME-Init: Gamma-Moment Equalization for LoRA Initialization in Parameter-Efficient Fine-Tuning. [PDF]

Entropy (Basel)
Lin Y, Li C, Shen Z, Liu J, Zeng M.
europepmc   +1 more source

Accelerated Discovery of Topological Spin Phase Diagrams in CrSBr Magnets Via High‐Throughput Optimization

Advanced Functional Materials, EarlyView.
Here, we develop a high‐throughput algorithm that accelerates the elucidation of phase diagrams of topological spin textures using limited computational resources at high numerical accuracy. Applying this framework to the van der Waals magnet CrSBr, we unveiled a hierarchy of previously unknown topological textures (domain‐wall bimerons, bimeron chains,
Andrew Lyall, Mohammad H. Badarneh, Cristian Bonato, Rebecca Cheung, Elton J. G. Santos   +4 more
wiley   +1 more source

SpatialPEFT: a parameter-efficient fine-tuning framework for spatial transcriptomics foundation models. [PDF]

Bioinformatics
Zou X, Lei X.
europepmc   +1 more source

Multi-Modal Parameter-Efficient Fine-tuning via Graph Neural Network

With the advent of the era of foundation models, pre-training and fine-tuning have become common paradigms. Recently, parameter-efficient fine-tuning has garnered widespread attention due to its better balance between the number of learnable parameters ...
Cheng, Bin, Lu, Jiaxuan
core  

Amphoteric Cu‐Doping Leading to High Thermoelectric Performance in p‐Type Bismuth Antimony Telluride

Advanced Functional Materials, EarlyView.
This study shows that Cu plays two opposite roles in p‐type Bi0.5Sb1.5Te3 depending on the processing route. Under thermodynamic‐equilibrium bulk‐synthesis, Cu mainly occupies cation sites, increases hole concentration, preserves mobility, and slightly reduces lattice heat transport. The best‐performing composition among the investigated series reaches
Moritz Thiem, Zhiyuan Li, Minsu Heo, Fangyi Hu, Tian Lan, Youngdeog Koh, Ruiwen Xie, Chuanmu Tian, Marc Widenmeyer, Hyun‐Sik Kim, Jan P. Hofmann, Yuan Yu, Hongbin Zhang, Anke Weidenkaff, G. Jeffrey Snyder, Wenjie Xie   +15 more
wiley   +1 more source

From "people also ask" to clarifying questions for conversational search using parameter-efficient fine-tuning and prompt engineering. [PDF]

Int J Digit Libr
Ecevit IS, Bedi NS, Sekulic I, Crestani F.   +3 more
europepmc   +1 more source

Sacrificial‐Layer‐Assisted Heat‐Affected‐Zone Suppression in Laser Patterning of PET for High‐Performance Flexible Devices

Advanced Functional Materials, EarlyView.
A removable sacrificial polymer layer engineers the thermal boundary condition during nanosecond laser ablation of PET, suppressing heat‐affected‐zone formation without relying on costly ultrafast lasers. This strategy enables deep, high‐aspect‐ratio trenches with no detectable heat‐affected zone, templating silver‐filled mesh electrodes with record ...
Mehdi Zarei, Mirza Sahaluddin, Mostafa Bedewy, Paul W. Leu   +3 more
wiley   +1 more source

PeFoMed: Parameter efficient fine-tuning of multimodal large language models for medical CXR. [PDF]

Sci Rep
Liu G, Tang X, He J, Li P, Chen Z, Zhong S.   +5 more
europepmc   +1 more source

Parameter Efficient Quasi-Orthogonal Fine-Tuning via Givens Rotation [PDF]

With the increasingly powerful performances and enormous scales of pretrained models, promoting parameter efficiency in fine-tuning has become a crucial need for effective and efficient adaptation to various downstream tasks.
Gao, Xin, Yang, Zhibang, Lin, Yang, Zhao, Junfeng, Ma, Xinyu, Chu, Xu   +5 more
core