Results 1 to 10 of about 1,764,417 (289)

Fine-tuning metabolic switches.

PLoS Biology, 2013
Cells get the energy for most of their activities in the form of adenosine triphosphate (ATP), which is generated through the breakdown of glucose and lipid molecules. Partial breakdown of a single glucose molecule through glycolysis yields 2 ATP molecules; and when glycolysis is followed by pyruvate decarboxylation and the tricarboxcylic acid (TCA ...
Caitlin Sedwick
doaj   +3 more sources

Adults with reading difficulties demonstrate selective impairments in the fine neural tuning for print

Frontiers in Neuroscience
IntroductionNeural tuning for print, reflected in differential responses of the N170 component of event-related potentials to orthographic forms and other visual stimuli, serves as the neural basis for efficient visual word reading.
Tongjie Zhuang, Yaowen Li, Yufei Tan, Jiuju Wang, Xiuyue Yue, Licheng Xue, Jing Zhao, Jing Zhao   +7 more
doaj   +1 more source

Generalization from Low- to Moderate-resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI

The Astrophysical Journal
Cross-survey generalization is a critical challenge in stellar spectral analysis, particularly in cases such as transferring from low- to moderate-resolution surveys. We investigate this problem using pretrained models, focusing on simple neural networks
Xiaosheng Zhao, Yuan-Sen Ting, Rosemary F.G. Wyse, Alexander S. Szalay, Yang Huang, László Dobos, Tamás Budavári, Viska Wei   +7 more
doaj   +1 more source

Prediction of software bug severity using transformers and sentiment signals

Journal of Intelligent Systems
Software bugs adversely affect software quality, security, and release schedules. Accurately predicting bug severity can improve triage and resource allocation.
Duwairi Rehab, Al-Mallak Shatha, Suleiman Husam   +2 more
doaj   +1 more source

Evaluating the Impact of Adapter-Based Fine-Tuning on Structured Parsing Performance in Large Language Models

Machine Learning and Knowledge Extraction
Recent advances in large language models (LLMs) highlight two dominant strategies for performance improvement: prompt engineering and fine-tuning. While prompt design can significantly influence model output, it remains uncertain whether lightweight fine-
Ratomir Karlović, Luka Sever, Sandi Baressi Šegota, Vedran Mrzljak, Ivan Lorencin   +4 more
doaj   +1 more source

Leveraging Low-Rank Adaptation for Parameter-Efficient Fine-Tuning in Multi-Speaker Adaptive Text-to-Speech Synthesis

IEEE Access
Text-to-speech (TTS) technology is commonly used to generate personalized voices for new speakers. Despite considerable progress in TTS technology, personal voice synthesis remains problematic in achieving high-quality custom voices.
Changi Hong, Jung Hyuk Lee, Hong Kook Kim   +2 more
doaj   +1 more source

Memorization in large language models in medicine prevalence characteristics and implications

Nature Communications
Large Language Models (LLMs) have demonstrated significant potential in medicine, with many studies adapting them through continued pretraining or fine-tuning on medical data.
Anran Li, Lingfei Qian, Mengmeng Du, Yu Yin, Yan Hu, Zihao Sun, Yihang Fu, Hyunjae Kim, Erica Stutz, Xuguang Ai, Qianqian Xie, Rui Zhu, Jimin Huang, Yifan Yang, Siru Liu, Yih-Chung Tham, Lucila Ohno-Machado, Hyunghoon Cho, Zhiyong Lu, Hua Xu, Qingyu Chen   +20 more
doaj   +1 more source

ANALYSIS OF WHISPER AUTOMATIC SPEECH RECOGNITION PERFORMANCE ON LOW RESOURCE LANGUAGE

Pilar Nusa Mandiri
Implementing Automatic Speech Recognition Technology in daily life could give convenience to its users. However, speeches that can be recognized accurately by the ASR model right now are in languages considered high resources, like English.
Riefkyanov Surya Adia Pratama, Agit Amrullah   +1 more
doaj   +1 more source

The impact of fine-tuning paradigms on unknown plant diseases recognition

Scientific Reports
Plant diseases pose significant threats to agriculture, impacting both food safety and public health. Traditional plant disease detection systems are typically limited to recognizing disease categories included in the training dataset, rendering them ...
Jiuqing Dong, Alvaro Fuentes, Heng Zhou, Yongchae Jeong, Sook Yoon, Dong Sun Park   +5 more
doaj   +1 more source

Assessing the Effectiveness of Transfer Learning in Chest X-Ray Analysis With the BRAX Dataset

IEEE Access
The integration of machine learning techniques in medicine has significantly enhanced medical diagnostics, making them more efficient, agile, and accurate.
Elton Douglas Silva, Thiago B. Pereira, Carlos Eduardo Brandao, Francisco De Assis Boldt, Thiago M. Paixao   +4 more
doaj   +1 more source