Results 131 to 140 of about 9,649,421 (248)

QuantFT-VL: Harmonizing Quantization and LoRA for Efficient Mobile Vision–Language Model Fine-Tuning

Algorithms
Vision–language models (VLMs) are increasingly deployed in resource-constrained environments, yet efficient fine-tuning remains challenging because post-training quantization often degrades the effectiveness of low-rank adaptation.
Fangyuan Jin, Hui Lin, Lu Zhang, Yiwei Chen   +3 more
doaj   +1 more source

LoREnc: Low-Rank Encryption for Securing Foundation Models and LoRA Adapters

Accepted to ICIP ...
Ahn, Beomjin, Kwon, Jungmin, Jung, Chanyong, Chung, Jaewook   +3 more
openaire   +2 more sources

RST-LoRA: A Discourse-Aware Low-Rank Adaptation for Long Document Abstractive Summarization

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
For long document summarization, discourse structure is important to discern the key content of the text and the differences in importance level between sentences. Unfortunately, the integration of rhetorical structure theory (RST) into parameter-efficient fine-tuning strategies for long document summarization remains unexplored.
Dongqi Liu 0001, Vera Demberg
openaire   +3 more sources

Fixing disconnects: Exploring the emergence of principled adaptations in a competency‐based curriculum

Medical Education, Volume 59, Issue 4, Page 428-438, April 2025.
Abstract Purpose Competency‐based medical education (CBME) promises to improve medical education through curricular reforms to support learner development. This intention may be at risk in the case of a Canadian approach to CBME called Competence by Design (CBD), since there have been negative impacts on residents. According to Joseph Schwab, teachers,
Mary C. Ott, Lori Dengler, Kathryn Hibbert, Michael Ott   +3 more
wiley   +1 more source

AI foundation models in plant biology

New Phytologist, EarlyView.
Foundation models decode genomes, engineer proteins, phenotype crops, and drive AI agents across plant biology. This figure was created in BioRender (BioRender.com/xcmmkel). Summary Rapid technological progress has enabled plant biologists to accumulate unprecedented volumes of multi‐scale, multi‐modal data, yet this abundance of data has intensified ...
Haopeng Yu
wiley   +1 more source

HierAnom‐Path: Zero‐Shot Rare Cancer Detection in Histopathology via Hierarchical Foundation Model Adaptation

Computational and Systems Oncology, Volume 6, Issue 1, December 2026.
ABSTRACT Rare cancers collectively represent 20%–25% of all malignancies yet yield fewer than 50 annotated whole‐slide images (WSIs) per subtype in publicly available archives, rendering supervised deep learning inapplicable. We present HierAnom‐Path, to the best of our knowledge, the first framework for zero‐shot rare cancer anomaly detection in ...
Noora Saleem Jumaah, Mohanad Sameer Jabbar, Saif H. Alwaeli, Noor Ayesha, Mohamed Babiker A. Mohamed, Muhammad I. Khan   +5 more
wiley   +1 more source

Cross‐Modal Artificial Intelligence Integrating Dynamic MRI and Clinical Data for Breast Cancer Diagnosis and Nodal Metastasis Prediction

MedComm – Oncology, Volume 5, Issue 4, December 2026.
A multicenter artificial intelligence framework was developed and externally validated for breast lesion classification and axillary lymph node metastasis prediction. Using dynamic contrast‐enhanced MRI alone for lesion classification and integrating MRI with preoperative clinical and biopsy‐derived information for nodal prediction, the framework ...
Wei Ren, Zifan He, Zhixian Deng, Zhenjun Huang, Gengxi Cai, Xiaohua Ban, Qiugen Hu, Zebang Zhang, Luhui Mao, Yujie Tan, Qing Peng, Zehua Wang, Ruichong Lin, Xian Yang, Xiaohui Duan, Herui Yao, Yunfang Yu   +16 more
wiley   +1 more source

SDS-LoRA: Overcoming Anisotropic Gradient Scaling in Low-Rank Adaptation

Low-Rank Adaptation (LoRA) enables efficient adaptation of large pre-trained models to downstream tasks by parameterizing weight updates with low-rank matrices. In this paper, we investigate the limitations of the LoRA parameterization from a geometric perspective. Specifically, we show that when a full fine-tuning gradient is backpropagated to the low-
Oh, Junghun, Baik, Sungyong, Lee, Kyoung Mu   +2 more
openaire   +2 more sources

Artificial intelligence‐powered plant phenomics: Progress, challenges, and opportunities

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Artificial intelligence (AI), a key driver of the Fourth Industrial Revolution, is being rapidly integrated into plant phenomics to automate sensing, accelerate data analysis, and support decision‐making in phenomic prediction and genomic selection.
Xu Wang, Daeun Choi, Damian Adams, Jaehyun Ahn, Kelly Balmant, Raquel Dias, Carlos D. Messina, Rafael Muñoz‐Carpena, Vance M. Whitaker, Haipeng Yu, Ziwen Yu, Chang Zhao, Changying Li   +12 more
wiley   +1 more source

AI‐Mediated Multimodal Reading Education for EFL Learners: Effects on Students' Enjoyment and Engagement

European Journal of Education, Volume 61, Issue 4, December 2026.
ABSTRACT Artificial intelligence (AI) has increasingly reshaped educational practices by expanding opportunities for adaptive, multimodal and learner‐centered instruction. While growing attention has been paid to AI‐supported language learning, less is known about how multimodal AI technologies may support the emotional and behavioural dimensions of ...
Lei Pan, Hangbo Zhao, Mehmet Sengul
wiley   +1 more source