Results 61 to 70 of about 9,716,149 (241)

Aspect Sentiment Triplet Extraction Combining Chain-of-Thought and Low-Rank Adaptation Fine-Tuning [PDF]

Jisuanji gongcheng
The Aspect Sentiment Triplet Extraction (ASTE) task is an important subtask of aspect-level sentiment analysis. Conventional supervised learning methods achieve SOTA or near-SOTA results in this task.
Biqing ZENG, Pengfei CHEN, Yongtao YAO
doaj   +1 more source

From mice to humans—divergent strategies for intestinal homeostasis and regeneration

FEBS Letters, EarlyView.
Recent advances such as organoid genome editing, xenotransplantation, imaging, and whole‐genome sequencing have enabled direct studies of human intestinal stem cells (ISCs). These studies reveal species‐specific features, including slower ISC proliferation, distinct injury responses, slower somatic mutation accumulation in humans, and an inverse ...
Keiko Ishikawa, Shinya Sugimoto, Toshiro Sato   +2 more
wiley   +1 more source

AULoRA: Anomaly Understanding With Low-Rank Adaptation for Zero-Shot Anomaly Detection

IEEE Access
Zero-Shot Anomaly Detection (ZSAD) aims to identify anomalies in unseen categories or scenarios. Recently, Vision-Language Models (VLMs), most notably CLIP, have been utilized to enhance anomaly detection performance.
Seunghyun Oh, Seongsu Lee, Seunghye Chae, Youngmin Ro   +3 more
doaj   +1 more source

Structural insights and therapeutic targets in Acinetobacter baumannii capsule biosynthesis

FEBS Letters, EarlyView.
Hypervirulent KL49 A. baumannii's capsular polysaccharide contains the nonulosonic acid 8‐epi‐Leg5,7Ac2, synthesized by epimerization via ElaA, ElaB, and ElaC. Crystal structures of ElaA, ElaB, and ElaC reveal their role in CMP‐Leg5,7Ac2 synthesis and regioselective C8 epimerization.
Woo Cheol Lee, Junho Jeong, Chae Yeong Lee, Hyunjoon Cho, Man Hwan Oh, Je Chul Lee, Jee‐Young Lee, Yangmee Kim   +7 more
wiley   +1 more source

Structured low-rank approximation with missing data

The approach of SIAM J. Matrix Anal. Appl., 26(4):1083--1099 for solving structured total least squares problems is generalized to weighted structured low-rank approximation with missing data. The method proposed is based on elimination of the correction
Markovsky, Ivan, Usevich, Konstantin
core   +1 more source

Modelling stem cell differentiation related processes—A practical overview for biologists

FEBS Letters, EarlyView.
Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar, Xinqi Yan, Lucas F. Jansen Klomp, Stefano Schivo, Janine N. Post   +4 more
wiley   +1 more source

Quantized Low-Rank Adaptation in Large Language Models for Clinical Text Simplification

International Journal of Computational Intelligence Systems
Simplifying medical language is vital for effective healthcare communication, as patients often find it hard to understand complex clinical terms and lengthy, information-rich sentences.
Parvathaneni Naga Srinivasu, Akshar Samudrala, Pinapati Gagan Devesh, Surakanti Advaith Reddy, Ahmed Al Nuaim   +4 more
doaj   +1 more source

Design and analysis strategies for robust microbiome ageing research

FEBS Letters, EarlyView.
The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik, İsmail Güderer, Yi Wang, Tayyaba Alvi, Prasoon Pandey, Handan Melike Dönertaş   +5 more
wiley   +1 more source

The Expressive Power of Low-Rank Adaptation [PDF]

Low-Rank Adaptation (LoRA), a parameter-efficient fine-tuning method that leverages low-rank adaptation of weight matrices, has emerged as a prevalent technique for fine-tuning pre-trained models such as large language models and diffusion models ...
Lee, Kangwook, Zeng, Yuchen
core   +1 more source

SA-LoRA: Shared-A decoupled low-rank adaptation for class-incremental learning

Journal of King Saud University: Computer and Information Sciences
Parameter-efficient fine-tuning methods have shown promise for continual learning with pre-trained models, yet existing approaches either sacrifice performance or incur linear parameter growth with task count.
Xiaohuan Bing, Yuanhao Xi, Ramin Yahyapour   +2 more
doaj   +1 more source