Suchergebnisse - "Large language model (LLM)"

Literate Programming with LLMs? - A Study on Rosetta Code and CodeNet

Autoren: Sun, Simin Staron, Miroslaw

Quelle: IEEE Transactions on Software Engineering. In Press

Schlagwörter: Code-related Tasks, Literate Programming, Computation Experiment, Large Language Model(LLM)

Dateibeschreibung: electronic

Zugangs-URL: https://research.chalmers.se/publication/549267
https://research.chalmers.se/publication/549267/file/549267_Fulltext.pdf

Federated Learning for Medical Applications: A Taxonomy, Current Trends, Challenges, and Future Research Directions

Autoren: Rauniyar, Ashish Hagos, Desta Haileselassie Jha, Debesh et al.

Quelle: IEEE Internet of Things Journal. 11(5):7374-7398

Schlagwörter: Medical services, Medical diagnostic imaging, Biomedical equipment, Data privacy, Surveys, Internet of Things, Cancer, Artificial intelligence (AI), communication, data privacy, edge computing, federated learning (FL), foundational model (FMs), large language model (LLM), medical applications, security

Dateibeschreibung: print

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-345592
https://doi.org/10.1109/JIOT.2023.3329061

Indigenous (Mis)Representation in Emerging LLM Research Methodologies

Autoren: Hanson, Zachary Arao

Quelle: UC Riverside Undergraduate Research Journal. 19(1)

Schlagwörter: Indigenous representation, Western film history, Artificial Intelligence, Large-Language Model (LLM), Internet research efficacy, History education

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/76f405pz
https://escholarship.org/content/qt76f405pz/qt76f405pz.pdf

Fine-tuned Vision Transformers and YOLOv11 for precise detection of pediatric Adenoid Hypertrophy

Autoren: Shaymaa E. Sorour Mohammed Aljaafari Abdullah A. Alarfaj et al.

Quelle: Alexandria Engineering Journal, Vol 128, Iss, Pp 366-393 (2025)

Schlagwörter: Adenoid Hypertrophy (AH), Data augmentation, Vision Transformers (ViT), YOLOv11, Large language model (LLM), Fine-tuning, TA1-2040, Engineering (General). Civil engineering (General)

Zugangs-URL: https://doaj.org/article/e99d5da89d8a4f27844eb86bc6abceb0

AI-Powered Transcreation in Global Marketing: Insights from Iran

Autoren: Ghodrat Hassani Marziyeh Malekshahi Hossein Davari

Quelle: ELOPE, Vol 22, Iss 1 (2025)

Schlagwörter: transcreation, English language, large language model (LLM), copywriting, GPT-3, PE1-3729, English literature, PR1-9680, marketing translation

Zugangs-URL: https://doaj.org/article/88feaec216124e7883f272283b0cfef5

Comparative Analysis of RAG-Based Open-Source LLMs for Indonesian Banking Customer Service Optimization Using Simulated Data

Autoren: Hendra Lijaya Patricia Ho Handri Santoso

Quelle: Jurnal Sisfokom, Vol 14, Iss 3, Pp 330-341 (2025)

Schlagwörter: semantic similarity, large language model (llm), llm-as-a-judge, retrieval-augmented generation (rag), Information technology, bank customer service, T58.5-58.64

Zugangs-URL: https://doaj.org/article/529ee024a1954c7d800398dad3d44bf3

Bootstrapping Text-to-SQL Resources for Knowledge Graph Question Answering

Autoren: Kosten, Catherine Davide, Lanti Cudré-Mauroux, Philippe et al.

Quelle: 2025 IEEE Swiss Conference on Data Science (SDS). :8-15

Schlagwörter: Text-to-SQL, Digitalisierung, Knowledge graph question answering, Large language model (LLM), Natural language processing, Knowledge graphs, Language models, 005: Computerprogrammierung, Programme und Daten, 006: Spezielle Computerverfahren

Exploring Chatbot Applications in Pancreatic Disease Treatment: Potential and Pitfalls

Autoren: Balduzzi, Alberto Pastena, Matteo De Tondato, Susanna et al.

Quelle: Artificial Intelligence Surgery. 5:377-86

Schlagwörter: Leveraging large language model (LLM), artificial intelligence, pancreas, pancreatic ductal adenocarcinoma, guidelines

Zugangs-URL: https://hdl.handle.net/11562/1167828
https://doi.org/10.20517/ais.2025.11

SVMFN-FSAR: Semantic-Guided Video Multimodal Fusion Network for Few-Shot Action Recognition

Autoren: Ran Wei Rui Yan Hongyu Qu et al.

Quelle: Big Data Mining and Analytics, Vol 8, Iss 3, Pp 534-550 (2025)

Schlagwörter: action recognition, large language model (llm), Electronic computers. Computer science, transformer, few-shot learning, video understanding, QA75.5-76.95

Zugangs-URL: https://doaj.org/article/4cfcad33e6cb403f91dbd3961ace50a1

DeepDiveAI: Identifying AI-Related Documents in Large Scale Literature Dataset

Autoren: Xingzhou Liang Xiaochen Zhou Hui Zou et al.

Quelle: Journal of Social Computing, Vol 6, Iss 2, Pp 158-169 (2025)

Schlagwörter: Social sciences (General), H1-99, FOS: Computer and information sciences, text classification, Artificial Intelligence (cs.AI), large language model (llm), Computer Science - Artificial Intelligence, Electronic computers. Computer science, long short-term memory (lstm), bidirectional encoder representations from transformers (bert), QA75.5-76.95, ai-related document

Zugangs-URL: http://arxiv.org/abs/2408.12871
https://doaj.org/article/836bcc6172e2486fbc8ad30eae3489f7

AI-powered life insurance claims adjudication using LLMs and RAG Architectures

Autoren: Madugula, Sita Rama Praveen Malali, Nihar

Quelle: International Journal of Science and Research Archive. 15:460-470

Schlagwörter: Machine Learning, Insurance Claims, Artificial Intelligence, Large Language Model (LLM), Life Insurance, Retrieval-Augmented Generation (RAG), Natural Language Processing

Design and application of a semantic-driven geospatial modeling knowledge graph based on large language models

Autoren: Jianyuan Liang Shuyang Hou Anqi Zhao et al.

Quelle: Geo-spatial Information Science, Pp 1-20 (2025)

Schlagwörter: QB275-343, domain knowledge, Large language model (LLM), geospatial modeling, intelligent generation, Mathematical geography. Cartography, knowledge graph construction, GA1-1776, Geodesy

Zugangs-URL: https://doaj.org/article/3f5ce10d992b4ce1b53d82a73bd38e1d

PE-GPT: A New Paradigm for Power Electronics Design

Autoren: Fanfan Lin Xinze Li Weihao Lei et al.

Quelle: Lin, F, Li, X, Lei, W, Rodriguez-Andina, J J, Guerrero, J M, Wen, C, Zhang, X & Ma, H 2025, 'PE-GPT : A New Paradigm for Power Electronics Design', IEEE Transactions on Industrial Electronics, vol. 72, no. 4, pp. 3778-3791. https://doi.org/10.1109/TIE.2024.3454408

Schlagwörter: Large language model (LLM), multimodal AI, power electronics (PE) design, power converter design, physics-informed AI

Zugangs-URL: https://vbn.aau.dk/da/publications/1574cd3a-a83e-469b-b684-37f9b266dc31
http://www.scopus.com/inward/record.url?scp=85205933140&partnerID=8YFLogxK
https://doi.org/10.1109/TIE.2024.3454408

Large Language Model for Medical Images: A Survey of Taxonomy, Systematic Review, and Future Trends

Autoren: Peng Wang Wenpeng Lu Chunlin Lu et al.

Quelle: Big Data Mining and Analytics, Vol 8, Iss 2, Pp 496-517 (2025)

Schlagwörter: large language model (llm), x-stage tuning, Electronic computers. Computer science, medical images, QA75.5-76.95

Zugangs-URL: https://doaj.org/article/9e6153343cae4ab9b486c29824982fde

MARLIN: Mixed-Precision Auto-Regressive Parallel Inference on Large Language Models

Autoren: Elias Frantar Roberto L. Castro Jiale Chen et al.

Quelle: PPoPP '25: Proceedings of the 30th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming

Schlagwörter: FOS: Computer and information sciences, Large language model (LLM) inference, GPU programming, Batch parallelism, Computer Science - Machine Learning, Machine Learning (cs.LG)

Dateibeschreibung: application/application/pdf

Zugangs-URL: http://arxiv.org/abs/2408.11743
http://hdl.handle.net/20.500.11850/729444

A Knowledge Graph Enhanced Pre-Trained Large Language Model for Predicting MicroRNA-circRNA Interactions

Autoren: Jiren Zhou Rui Niu Boya Ji et al.

Quelle: Big Data Mining and Analytics, Vol 8, Iss 6, Pp 1405-1417 (2025)

Schlagwörter: knowledge graph, sequential large language model (llm), graph contrastive learning, circrna-microrna interactions, self-supervised neural network, Electronic computers. Computer science, QA75.5-76.95

Dateibeschreibung: electronic resource

Relation: https://www.sciopen.com/article/10.26599/BDMA.2025.9020014; https://doaj.org/toc/2096-0654; https://doaj.org/toc/2097-406X

Zugangs-URL: https://doaj.org/article/121e60467ff5404e9e7905ce5a47df1f

Diagnostic Accuracy and Counseling Quality of GPT-4o for Strabismus and Pseudostrabismus in Patient-Generated Mobile Photographs: A Preliminary Evaluation

Autoren: Esposito EP Cardakli N Christoff A et al.

Quelle: Clinical Ophthalmology, Vol 19, Iss Issue 1, Pp 4077-4084 (2025)

Schlagwörter: Pediatric ophthalmology, strabismus, large language model (LLM), artificial intelligence (AI), patient education, Ophthalmology, RE1-994

Dateibeschreibung: electronic resource

Relation: https://www.dovepress.com/diagnostic-accuracy-and-counseling-quality-of-gpt-4o-for-strabismus-an-peer-reviewed-fulltext-article-OPTH; https://doaj.org/toc/1177-5483

Zugangs-URL: https://doaj.org/article/d89311c234224a83bcd3e82cd9467daf

Optical Character Recognition Evaluation for Historical Archival Records

Autoren: Kelsch, Madeline Hall, Madison York, Conor et al.

Schlagwörter: Federal Statistics, Large Language Model (LLM), Optical Character Recognition (OCR), Computer vision

LLM based expert AI agent for mission operation management

Autoren: Sobhana Mummaneni Syama Sameera Gudipati Satwik Panda

Quelle: Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, Vol 15, Iss 1 (2025)

Schlagwörter: Environmental sciences, Large Language Model (LLM), telemetry data, mission operation management, Environmental engineering, expert AI agent, GE1-350, TA170-171, artificial intelligence, Retrieval Augmented Generation (RAG)

Zugangs-URL: https://doaj.org/article/b5bdee1be28e43cabbf7bc35b3ade258

Normalized difference vegetation index prediction using reservoir computing and pretrained language models

Autoren: John Olamofe Ram Ray Xishuang Dong et al.

Quelle: Artificial Intelligence in Agriculture, Vol 15, Iss 1, Pp 116-129 (2025)

Schlagwörter: Reservoir computing (RC), Temporal prediction, GPT2, NDVI, Large language model (LLM), Deep learning (DL), Agriculture

Zugangs-URL: https://doaj.org/article/29152a11148b4db19ffa656ac6cf2448