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AI Magazine, Volume 47, Issue 3, Fall 2026.Abstract The rapid proliferation of smart‐city ecosystems has significantly amplified the demand for Li‐ion batteries, which now serve as the primary energy source for sustainable transportation systems such as e‐bikes. Ensuring battery safety and optimal performance is crucial, yet challenging due to complex intrinsic dynamics and extrinsic operating ...
Zhao Li +3 more
wiley +1 more source
Proceedings of the International Florida Artificial Intelligence Research Society ConferenceRetrieval-Augmented Generation (RAG) is a commonly used, cost-effective solution for supplementing domain-focused knowledge for Large Language Models (LLMs), but contemporary RAG implementations often suffer from inconsistent accuracy and performance ...
Yeriel Rhee +3 more
doaj
Talking trails: LLM‐enhanced spatiotemporal trajectory modeling for E‐bike delivery route planning
AI Magazine, Volume 47, Issue 3, Fall 2026.Abstract Electric bicycles (e‐bikes) have become the dominant mode of transportation in China's urban instant delivery industry. However, many riders lack the experience to navigate complex traffic networks and diverse road conditions, leading to reduced delivery efficiency.
Zhao Li +3 more
wiley +1 more source
HiSem-RAG: A Hierarchical Semantic-Driven Retrieval-Augmented Generation Method
Traditional retrieval-augmented generation (RAG) methods struggle with hierarchical documents, often causing semantic fragmentation, structural loss, and inefficient retrieval due to fixed strategies.
Dongju Yang, Junming Wang
core +1 more source
RAG-Check: Evaluating Multimodal Retrieval Augmented Generation Performance [PDF]
Retrieval-augmented generation (RAG) improves large language models (LLMs) by using external knowledge to guide response generation, reducing hallucinations.
Mortaheb, Matin +3 more
core +2 more sources
Privacy‐preserving multi‐agent systems for human‐centred inclusive healthcare AI
AI Magazine, Volume 47, Issue 3, Fall 2026.ABSTRACT Healthcare environments present uniquely demanding constraints for the deployment of artificial intelligence (AI). Clinical decisions of significant consequence are rarely the product of a single isolated computation; rather, safe and effective patient care relies on the continuous collaboration of distributed entities, including clinicians ...
Mufti Mahmud +14 more
wiley +1 more source
Retrieval-Augmented Generation: Strengthening Answer Confidence through Source Referencing
reservedThis thesis presents the design of a Retrieval-Augmented Generation (RAG) system and proposes an evaluation strategy to assess its performance in open-domain Question Answering (QA).
CECCATO, ANDREA
core
Advanced Intelligent Systems, Volume 8, Issue 9, September 2026.An agentic AI‐driven decision‐support framework for prosumers is proposed, integrating PV generation, load profiling, and multihorizon optimization within a four‐agent architecture. The approach significantly reduces grid dependence, enhances self‐sufficiency and prevents system oversizing.
Adela BÂRA, Simona‐Vasilica OPREA
wiley +1 more source
CommunityKG-RAG: Leveraging Community Structures in Knowledge Graphs for Advanced Retrieval-Augmented Generation in Fact-Checking [PDF]
Despite advancements in Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems, their effectiveness is often hindered by a lack of integration with entity relationships and community structures, limiting their ability to provide ...
Chang, Rong-Ching, Zhang, Jiawei
core +1 more source
Computer Applications in Engineering Education, Volume 34, Issue 5, September 2026.ABSTRACT Simulation‐based games are widely used in engineering and management studies to support decision‐making in complex and dynamic environments. This study presents an exploratory case study of the design, implementation, and evaluation of a Retrieval‐Augmented Generation (RAG) assistant that uses 10 years of instructor‐answered student questions ...
Toni Tani +3 more
wiley +1 more source