Results 21 to 30 of about 3,227,651 (213)

An Event-Driven Dual-Mode Multilingual RAG Framework for Industrial Maintenance

IEEE Access
Industrial equipment fault diagnosis faces critical challenges in non-English operational environments. This paper presents an Event-Driven Dual-Mode Multilingual Retrieval-Augmented Generation (EDM-RAG) framework for industrial maintenance.
Ya-Jou Cheng, Shang-Liang Chen
doaj   +1 more source

MAPA: A Semantic Network Framework for Functional Module Discovery and Interpretation in Multi‐Omics Data

Advanced Science, EarlyView.
MAPA transforms complex multi‐omics data into biologically coherent functional modules by integrating pathway information with molecular interaction networks. Retrieval‐augmented large language models then generate structured, literature‐informed interpretations.
Yifei Ge, Feifan Zhang, Yijiang Liu, Chao Jiang, Peng Gao, Nguan Soon Tan, Sai Zhang, Yuchen Shen, Qianyi Zhou, Xin Zhou, Xiao Wang, Fangqing Zhao, Chuchu Wang, Xiaotao Shen   +13 more
wiley   +1 more source

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

Advanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee, Hyeonbin Moon, Junhyeong Lee, Seunghwa Ryu   +3 more
wiley   +1 more source

LIGHTWEIGHT RETRIEVAL AUGMENTED GENERATION (RAG) EVALUATION PIPELINE [PDF]

Retrieval Augmented Generation (RAG) pipelines reduce the frequency of Large Language Model (LLM) hallucinations by grounding the LLM context in knowledge base documents.
Kroll, Margaret, Kraus, Kelsey
core   +1 more source

Swamped with Too Many Articles? GraphRAG Makes Getting Started Easy

AI
Background: Both early researchers, such as new graduate students, and experienced researchers face the challenge of sifting through vast amounts of literature to find their needle in a haystack.
Joëd Ngangmeni, Danda B. Rawat
doaj   +1 more source

LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?

Advanced Intelligent Discovery, EarlyView.
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler, Manuel Raimann, Marc Münker, Maxim Rosin, Joaquin E. Urrutia Gómez, Christof M. Niemeyer, Markus Reischl, Luca Rettenberger   +7 more
wiley   +1 more source

Tracert-Retrieval-Augmented Generation: Boosting Multi-Hop Retrieval-Augmented Generation with Direction-Aware Graph Traversal

Engineering Proceedings
Tracert-retrieval-augmented generation (RAG) is a novel retrieval-augmented framework designed for efficient, document-level multi-hop reasoning. Unlike conventional RAG systems that retrieve top-k text segments based solely on dense similarity, Tracert ...
Siu-Him Zhang, Jhe-Wei Lin
doaj   +1 more source

A Generalizable Framework for Building Executable Domain‐Specific Large Language Models Under Data Scarcity: Demonstration on Semiconductor Technology Computer‐Aided Design Simulation

Advanced Intelligent Systems, EarlyView.
A schema‐first alignment framework builds compact, executable domain‐specific language models under data scarcity. Large‐scale synthetic question‐answer generation instills domain knowledge, and a code‐centric IR‐to‐DPO pipeline aligns generation with tool‐executable syntax.
Di Wang, Zhenhua Wu, Yu Liu, Kai Chang, Shaohua Wu   +4 more
wiley   +1 more source

Accelerating the Roll‐Out of Modular Plants: From Engineering and Approval to Operation of Energy‐Efficient Modular Plants

Chemie Ingenieur Technik, EarlyView.
In the ENPRO REUNION project, a manufacturer‐independent modular plant concept was demonstrated by commissioning a pilot plant that integrated modules from different vendors and by expanding the module pool to include extraction and crystallization units.
Laura Marsollek, Mathias Schmitz, Sascha Lamm, Markus Heinbücher, Isabell Viedt, Shreyas Parbat, Peter Pelz, Leon Urbas, Norbert Kockmann   +8 more
wiley   +1 more source

Medical LLMs: Fine-Tuning vs. Retrieval-Augmented Generation

Bioengineering
Large language models (LLMs) are trained on huge datasets, which allow them to answer questions from various domains. However, their expertise is confined to the data that they were trained on. In order to specialize LLMs in niche domains like healthcare,
Bhagyajit Pingua, Adyakanta Sahoo, Meenakshi Kandpal, Deepak Murmu, Jyotirmayee Rautaray, Rabindra Kumar Barik, Manob Jyoti Saikia   +6 more
doaj   +1 more source