Results 141 to 150 of about 15,745,009 (280)

Deep Contrastive Learning for High‐Throughput Prediction of Drug Resistance Mutations from Sequences

Advanced Science, EarlyView.
This study presents DeepMutDTA, a deep learning framework aimed at predicting mutation‐induced changes in protein‐drug interactions and prioritizing variants potentially linked to drug resistance. Trained on large‐scale data, it incorporates SimSiam‐MuTF, a label‐aware contrastive fine‐tuning strategy that encourages separation between WT and MT ...
Xiaowen Hu, Pan Zhang, Shangqian Wu, Hao Sun, Minwei Li, Sophia Tsoka, Zizhang Sheng, Lei Deng   +7 more
wiley   +1 more source

Infrared and visible image fusion driven by multimodal large language models

Frontiers in Physics
IntroductionExisting image fusion methods primarily focus on obtaining high-quality features from source images to enhance the quality of the fused image, often overlooking the impact of improved image quality on downstream task performance.MethodsTo ...
Ke Wang, Dengshu Hu, Yuan Cheng, Yukui Che, Yuelin Li, Zhiwei Jiang, Fengxian Chen, Wenjuan Li   +7 more
doaj   +1 more source

MechRAG: a multimodal large language model for mechanical engineering

Communications Engineering
Abstract Engineering design and manufacture are inherently multimodal activities in which engineers consult and produce diverse data and representations across various engineering disciplines and product lifecycle stages. Although well-established digital formats exist for these representations, their use remains restricted within ...
Shuang Li, Jonathan Corney
openaire   +3 more sources

Visual Representation Alignment for Multimodal Large Language Models

CoRR
Multimodal large language models (MLLMs) trained with visual instruction tuning have achieved strong performance across diverse tasks, yet they remain limited in vision-centric tasks such as object counting or spatial reasoning. We attribute this gap to the prevailing text-only supervision paradigm, which provides only indirect guidance for the visual ...
Heeji Yoon, Jaewoo Jung, Junwan Kim, Hyungyu Choi, Heeseong Shin, Sangbeom Lim, Honggyu An, Chaehyun Kim, Jisang Han, Donghyun Kim, Chanho Eom, Sunghwan Hong, Seungryong Kim   +12 more
openaire   +2 more sources

Atomic Defects in Layered Transition Metal Dichalcogenides for Sustainable Energy Storage and the Intelligent Trends in Data Analytics

Advanced Science, EarlyView.
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo, Ying Yang, Zizhen Fu, Fengqi Liu, Susu Fang, Kele Xu, Shanshan Wang   +6 more
wiley   +1 more source

Towards Robust Instruction Tuning on Multimodal Large Language Models [PDF]

Fine-tuning large language models (LLMs) on multi-task instruction-following data has been proven to be a powerful learning paradigm for improving their zero-shot capabilities on new tasks.
Han, Wei, Chen, Hui, Poria, Soujanya
core   +1 more source

Symbolic regression with multimodal large language models and Kolmogorov–Arnold networks

Machine Learning: Science and Technology
We present a novel approach to symbolic regression using vision-capable large language models (LLMs) and the ideas behind Google DeepMind’s funsearch . The LLM is given a plot of a univariate function and tasked with proposing an ansatz for that function.
Thomas R Harvey, Fabian Ruehle, Cristofero S Fraser-Taliente, James Halverson   +3 more
doaj   +1 more source

Multimodal large language models in human-centered health: practical insights

Multimodal data offer a comprehensive view of human health by integrating diverse sources, such as text, medical images, physiological signals, and behavioral data.
Marcu, Gabriela, Dang, Ting, Jia, Hong
core   +1 more source

Charting Endocrine Progenitors Across Species and Organs

Advanced Science, EarlyView.
Endocrine progenitors give rise to the hormone‐producing cells of the pancreas and intestine. Using single‐cell multiomics and proteomics, this study compares these progenitors across species, systems, and organs, mapping the conserved and species‐specific gene regulatory networks that guide their formation.
Changying Jing, Michael Sterr, Özüm Sehnaz Caliskan, Lama Saber, Nicole Katarina Rogers, Samuel Ogden, Kei Kozawa, Christos Karampelias, Jessica Jaki, Aimée Bastidas‐Ponce, Falk Janos Farkas, Oliver Czarnecki, Osvaldo Rodrigues Pereira, Perla Cota, Valerie Vandenbempt, Diego Balboa, Anika Böttcher, Natalie Krahmer, Mohammad Lotfollahi, Julie B. Sneddon, Heiko Lickert, Mostafa Bakhti   +21 more
wiley   +1 more source

Enhancing core competencies in digital education by multimodal large language models

Discover Computing
Under the background of digital transformation of education, it has become a key issue to cultivate the core competence of digital teaching. However, the traditional digital teaching has limitations in situation creation, cognitive interaction and ...
Shaohua Li, Zhiming Zhang, Yanxia Shi, Chunlin Yao   +3 more
doaj   +1 more source