Results 71 to 80 of about 176,171 (277)

His‐MMDM: Multi‐Domain and Multi‐Omics Translation of Histopathological Images with Diffusion Models

Advanced Science, EarlyView.
His‐MMDM is a diffusion model‐based framework for scalable multi‐domain and multi‐omics translation of histopathological images, enabling tasks from virtual staining, cross‐tumor knowledge transfer, and omics‐guided image editing. ABSTRACT Generative AI (GenAI) has advanced computational pathology through various image translation models.
Zhongxiao Li, Tianqi Su, Bin Zhang, Wenkai Han, Sibin Zhang, Guiyin Sun, Yuwei Cong, Xin Chen, Jiping Qi, Yujie Wang, Shiguang Zhao, Hongxue Meng, Peng Liang, Xin Gao   +13 more
wiley   +1 more source

On Explainability of Cluster Prototypes with Rough Sets: A Case Study in the FMCG Market

International Journal of Applied Mathematics and Computer Science
Despite the growing popularity of machine learning (ML), such solutions are often incomprehensible to employees and difficult to control. Addressing this issue, we discuss some essential problems of explainable ML applications in the fast-moving consumer
Grzegorowski Marek, Janusz Andrzej, Marcinowski Łukasz, Skowron Andrzej, Ślęzak Dominik, Śliwa Grzegorz   +5 more
doaj   +1 more source

Method for constructing a cognitive map of processes in a dynamic system using the cooperation of large language models

Ìнформаційні технології та компʼютерна інженерія
In the context of growing demands for rapid decision-making and in-depth analysis of complex dynamic systems – particularly when available data are limited and the involvement of experienced experts is either impractical or prohibitively expensive – the ...
B. Varer, V. Mokin
doaj   +1 more source

User-LLM: Efficient LLM Contextualization with User Embeddings

Companion Proceedings of the ACM on Web Conference 2025
Large language models (LLMs) have achieved remarkable success across various domains, but effectively incorporating complex and potentially noisy user timeline data into LLMs remains a challenge. Current approaches often involve translating user timelines into text descriptions before feeding them to LLMs, which can be inefficient and may not fully ...
Lin Ning, Luyang Liu, Jiaxing Wu, Neo Wu, Devora Berlowitz, Sushant Prakash, Bradley Green, Shawn O'Banion, Jun Xie   +8 more
openaire   +2 more sources

Genetic Diagnosis and Discovery Enabled by Large Language Models

Advanced Science, EarlyView.
We demonstrate that large language models (LLMs) can facilitate genetic diagnosis and discovery. LLMs were used to solve four types of genetic problems of sequentially increased complexity. An LLM‐based pipeline could analyze genetic variants in the genomic sequences of human hearing loss or rare genetic disease patients and assist in identifying ...
Tao Tu, Khaled Saab, Weida Liu, Zhouqing Fang, Zhuanfen Cheng, Svetolik Spasic, Maja Djurisic, Hiroaki Mohri, Wenlong Ren, Anil Palepu, Juraj Gottweis, Alan Karthikesalingam, Kavita Kulkarni, Annalisa Pawlosky, Devon Bonner, Elijah Kravets, Shruti Marwaha, Hector R. Mendez, Matthew T. Wheeler, Jonathan A. Bernstein, Undiagnosed Diseases Network, Cheng‐Yu Tsai, Chen‐Chi Wu, Konstantina M. Stankovic, Vivek Natarajan, Gary Peltz   +25 more
wiley   +1 more source

Analysis of the capabilities of large and small language models (LLM/SLM) for optimizing decision-making processes in a radio communication system

Технічна інженерія
The modern radio communication system operates in conditions of extreme complexity, characterized by a dynamically changing environment, high density of information flows, and active enemy countermeasures.
S.O. Dupelich, V.V. Dzyubenko
doaj   +1 more source

CMS swaps in separable one-factor Gaussian LLM and HJM model [PDF]

An approximation approach to Constant Maturity Swaps (CMS) pricing in the separable one-factor Gaussian LLM and HJM models is presented. The approximation used is a Taylor expansion on the swap rate as a function of a random variable which is intuitively
Henrard, Marc
core   +1 more source

MicrobeDiscover: A Knowledge Graph–Enabled AI Framework for Identifying Microbes for Inorganic Nanomaterial Biosynthesis

Advanced Science, EarlyView.
Microbial synthesis of nanomaterials (NMs) is eco‐friendly, but the screening of microorganisms is limited by inefficient traditional methods (currently only involving∽400 microorganisms/90 NMs). We propose AI framework MicrobeDiscover, integrating a knowledge graph of microbe‐NM interactions.
Ludi Wang, Hexing Han, Yufeng Liu, Zhiyuan Ning, Yujie Ma, Haidan Wang, Jinling Xu, Qiansheng Huang, Wenjuan Cui, Yuanchun Zhou, Yang Gao, Bin Wang, Yi Du   +12 more
wiley   +1 more source

ChatGPT in Teaching Linear Algebra: Strides Forward, Steps to Go

Open Education Studies
As soon as a new technology emerges, the education community explores its affordances and the possibilities to apply it in education. In this article, we analyze sessions with ChatGPT around topics in basic linear algebra.
Bagno Eli, Dana-Picard Thierry (Noah), Reches Shulamit   +2 more
doaj   +1 more source

LLM Chemistry Estimation for Multi-LLM Recommendation

Multi-LLM collaboration promises accurate, robust, and context-aware solutions, yet existing approaches rely on implicit selection and output assessment without analyzing whether collaborating models truly complement or conflict. We introduce LLM Chemistry -- a framework that measures when LLM combinations exhibit synergistic or antagonistic behaviors ...
Sanchez, Huascar, Hitaj, Briland
openaire   +2 more sources