Results 101 to 110 of about 3,227,651 (213)

Optimizing Context and Cost in LLM‐Based Unit Test Generation: A Study on External Dependency Retrieval Strategies

Expert Systems, Volume 43, Issue 10, October 2026.
ABSTRACT While Large Language Models (LLMs) have demonstrated remarkable capabilities in code generation, their effectiveness in unit testing is often constrained by insufficient context regarding external dependencies. This limitation is particularly pronounced in industrial settings, where proprietary code remains opaque to the model. To address this
Javier Ferrer, Francisco Chicano
wiley   +1 more source

RAG in clinical practice: a cautionary tale of AI ‘Truthfulness’

npj Health Systems
Retrieval-augmented generation (RAG) aims to curb large language models (LLMs) hallucinations, yet its conversational reliability is uncertain. We tested a clinical RAG by executing the same query 100 times at varying dialogue lengths.
HyoJe Jung, Kyusok Cho, Tae Joon Jun, Young-Hak Kim   +3 more
doaj   +1 more source

SPR-RAG: Semantic Parsing Retriever-Enhanced Question Answering for Power Policy

Algorithms
To address the limitations of Retrieval-Augmented Generation (RAG) systems in handling long policy documents, mitigating information dilution, and reducing hallucinations in engineering-oriented applications, this paper proposes SPR-RAG, a retrieval ...
Yufang Wang, Tongtong Xu, Yihui Zhu
doaj   +1 more source

Cross‐Lingual Knowledge Transfer Framework for Multilingual Customer Support AI: An Expert System Perspective

Expert Systems, Volume 43, Issue 10, October 2026.
ABSTRACT This study presents a comprehensive methodology for processing multilingual customer support data to prepare it for training AI‐based conversational systems. Using a dataset of 36,599 unique customer interactions from a Finnish energy company, we employed language‐specific BERT models to identify and analyse thematic patterns within customer ...
Joona Mäntyvaara, Paavo Nevalainen, Jukka Heikkonen   +2 more
wiley   +1 more source

Efficacy Evaluation and Optimization of RAG Knowledge Bases in the Oil and Gas Industry Using an LLM-as-a-Judge Mechanism

Energies
The increasing adoption of Retrieval-Augmented Generation (RAG) in the oil and gas industry has created a growing need for systematic evaluation of domain-specific knowledge bases, particularly with respect to retrieval failures, numerical and entity ...
Tianxiang Yang, Yu Cao, Yingkai Ma, Yuan Liang, Tangqi Liu, Chi Qin, Xionghao Liao   +6 more
doaj   +1 more source

Large Language Models and Retrieval‐Augmented Platforms for the Diagnosis and Management of Periodontal Diseases: A Blinded Expert‐Rated Comparative Study of 11 Systems

Journal of Clinical Periodontology, Volume 53, Issue 10, Page 1546-1556, October 2026.
ABSTRACT Aim To compare retrieval‐augmented systems with general‐purpose large language models (LLMs) on standardised periodontal clinical vignettes. Materials and Methods Eleven AI systems were evaluated: nine general‐purpose LLMs, one general‐purpose retrieval‐augmented platform (Perplexity) and one medical‐domain retrieval‐augmented platform ...
Yaniv Mayer, Bertha Demetriou, Giulio Rasperini, Eran Gabay, Rok Gašperšič, Darko Božić, Javier Calatrava, Ofir Ginesin, Hadar Zigdon Giladi, Ricardo Faria Almeida   +9 more
wiley   +1 more source

Evaluating RAG Performance on Small Language Models for Low-Resource Devices through Chunking and Retrieval Methods

JOIN: Jurnal Online Informatika
Retrieval-Augmented Generation (RAG) combines generative capabilities of language models with external document retrieval to answer questions grounded in reference texts.
Amelia Dewi Agustiani, Salsabila Maharani Putri, Jonner Hutahaean, Muhammad Rizqi Sholahuddin, Muhammad Riza Alifi, Ade Hodijah   +5 more
doaj   +1 more source

Evaluating Large Language Model‐Assisted Emergency Triage: A Comparison of Acuity Assessments by GPT‐4 and Medical Experts

Journal of Clinical Nursing, Volume 35, Issue 10, Page 4249-4255, October 2026.
ABSTRACT Aim To evaluate the accuracy of the Emergency Severity Index (ESI) assignments by GPT‐4, a large language model (LLM), compared to senior emergency department (ED) nurses and physicians. Method An observational study of 100 consecutive adult ED patients was conducted. ESI scores assigned by GPT‐4, triage nurses, and by a senior clinician. Both
Gal Ben Haim, Mor Saban, Yiftach Barash, David Cirulnik, Amit Shaham, Ben Zion Eisenman, Livnat Burshtein, Orly Mymon, Eyal Klang   +8 more
wiley   +1 more source

GEM-RAG: Graphical Eigen Memories For Retrieval Augmented Generation [PDF]

The ability to form, retrieve, and reason about memories in response to stimuli serves as the cornerstone for general intelligence - shaping entities capable of learning, adaptation, and intuitive insight.
Ferber, Aaron, Wang, Yingheng, Gomes, Carla, Rappazzo, Brendan Hogan   +3 more
core   +1 more source

Secure Multifaceted-RAG: Hybrid Knowledge Retrieval with Security Filtering

Information
Existing Retrieval-Augmented Generation (RAG) systems face challenges in enterprise settings due to limited retrieval scope and data security risks. When relevant internal documents are unavailable, the system struggles to generate accurate and complete ...
Grace Byun, Shinsun Lee, Nayoung Choi, Jinho D. Choi   +3 more
doaj   +1 more source