Results 121 to 130 of about 124,133 (290)
Pre-trained foundation models, trained on large-scale datasets, have demonstrated significant success in a variety of downstream vision tasks. Parameter-efficient fine-tuning (PEFT) methods aim to adapt these foundation models to new domains by updating ...
Jiuyu Zhang, Fan Lei, Xijian Fan
doaj +1 more source
Omnipolar Magnetic Field Detection by Superlattice‐Based Hall Sensor
Magnetic‐field‐induced electronic switching is demonstrated in unit‐cell‐engineered La0.7Sr0.3MnO3–BiFeO3 superlattices. Distinct substrate terminations modify magnetic and transport properties. Hall resistance measurements show omnipolar, hysteretic anomalous Hall switching above the Curie temperature, arising from Fe─Mn interfacial exchange, enabling
Mark Huijben +6 more
wiley +1 more source
Meta-Adapters: Parameter Efficient Few-shot Fine-tuning through Meta-Learning
Consistent improvements in the representational capacity of large pre-trained transformers has made it increasingly viable to serve these models as shared priors that can be fine-tuned on a large number of downstream tasks.
McCallum, Andrew +4 more
core
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
Memba: Membrane-driven Parameter-Efficient Fine-Tuning for Mamba
ICLR ...
Donghyun Lee 0002 +4 more
openaire +2 more sources
This study demonstrates that memristors can replace conventional 2T–1C driving circuits with simplified 1T–1 m architectures by exploiting resistance switching. With ultra‐low switching voltages (< ±0.2 V) and multi‐level resistance states, the memristors precisely control the current injected into organic light‐emitting diodes (OLEDs).
Dong Hyun Kim +6 more
wiley +1 more source
Background. Building upon previous research, this study conducts an exploration into Large Language Models (LLMs), with an emphasis on the fine-tuning and assessment of LLaMA-3.1 for instructional tasks. LLaMA-3.1, which is a new generation model and has
Bohdan Pavlyshenko, Ivan Bulka
doaj +1 more source
Wafer‐scale two‐dimensioanl In2Se3 oxidized into InOx on sodium‐embedded beta‐alumina enables multifunctional reconfigurable electronics. Sodium ions accumulate within distinct spatial distribution under drain‐controlle and gate‐controlled operation. Drain‐control operation gives controllability of ultraviolet‐driven optoelectronic synaptic conductance
Jinhong Min +13 more
wiley +1 more source
This paper presents a digital microfluidics‐based technique for transferring and reconfiguring soft nanomembranes. Laser‐machined nanothin membranes are picked up, transported, and aligned via tailored surface tension and the actuation of water droplets, enabling the development of flexible electronics, the integration of functional materials on 3D ...
Quang Anh Nguyen +15 more
wiley +1 more source
Field‐free spin‐orbit torque domain‐wall synapses integrated with stochastic MTJ neurons enable compact hardware Boltzmann machines. Leveraging intrinsic stochasticity and multi‐level conductance, the system achieves efficient probabilistic learning with high accuracy, demonstrating a scalable spintronic platform for energy‐efficient edge AI.
Aijaz H. Lone +8 more
wiley +1 more source

