Results 21 to 30 of about 36,775 (295)

Review of Document Q&A Driven by Multimodal Retrieval-Augmented Generation (Invited) [PDF]

Jisuanji gongcheng
Traditional Retrieval-Augmented Generation (RAG) methods predominantly focus on pure-text scenarios. In these scenarios, their retrieval and generation mechanisms encounter difficulties in effectively modeling common visual elements, spatial layouts, and
LI Zeming, WANG Shuliang, SHANG Zihe, SHENG Ming
doaj   +1 more source

Parametric Retrieval Augmented Generation

Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval
Retrieval-augmented generation (RAG) techniques have emerged as a promising solution to enhance the reliability of large language models (LLMs) by addressing issues like hallucinations, outdated knowledge, and domain adaptation. In particular, existing RAG methods append relevant documents retrieved from external corpus or databases to the input of ...
Weihang Su, Yichen Tang 0001, Qingyao Ai, Junxi Yan, Changyue Wang 0001, Hongning Wang, Ziyi Ye, Yujia Zhou 0002, Yiqun Liu 0001   +8 more
openaire   +2 more sources

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

Distributed Retrieval-Augmented Generation

CoRR
As large language models (LLMs) become increasingly adopted on edge devices, Retrieval-Augmented Generation (RAG) is gaining prominence as a solution to address factual deficiencies and hallucinations by integrating external knowledge. However, centralized RAG architectures face significant challenges in data privacy and scalability.
Chenhao Xu 0003, Longxiang Gao, Yuan Miao, Xi Zheng 0001   +3 more
openaire   +2 more sources

Next Sentence Prediction with BERT as a Dynamic Chunking Mechanism for Retrieval-Augmented Generation Systems

Proceedings of the International Florida Artificial Intelligence Research Society Conference
Retrieval-Augmented Generation systems enhance the generative capabilities of large language models by grounding their responses in external knowledge bases, addressing some of their major limitations and improving their reliability for tasks requiring ...
Alexandre Thurow Bender, Gabriel Almeida Gomes, Ulisses Brisolara Corrêa, Ricardo Matsumura Araujo   +3 more
doaj   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Artificial intelligence-driven clinical guideline recommendations in maternal care: How trustworthy are they?

Biomédica: revista del Instituto Nacional de Salud
Introduction. Medical staff often face difficulties in consulting and applying clinical guidelines in practice. Large language models, especially when combined with retrieval-augmented generation, may help overcome these challenges by producing context ...
Jairo J. Pérez, Andrés F. Giraldo-Forero, Santiago Rúa, Daniel Betancur, Zuliany Urquina, Pablo Castañeda, Sara Arango-Valencia, Juan Guillermo Barrientos-Gómez, Ever A. Torres-Silva, Andrés Orozco-Duque   +9 more
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Retrieval Augmented Recipe Generation

2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
ACCEPT on IEEE/CVF Winter Conference on Applications of Computer Vision (WACV ...
LIU, Guoshan, YIN, Hailong, ZHU, Bin, CHEN, Jingjing, NGO, Chong-wah, JIANG, Yu-Gang   +5 more
openaire   +2 more sources

Hybrid Solar Cell/Triboelectric Nanogenerator Based on Stable Two‐Dimensional Covalent Organic Frameworks

Advanced Functional Materials, EarlyView.
This study highlights the integration of stable two‐dimensional covalent organic framework (COF) films as photoactive layers in hybrid nanoenergy devices. The results demonstrate their capacity to generate electricity under both sunny and rainy conditions, showcasing versatility and resilience.
Joab D. Guerrero, Susana Ramos‐Terrón, Salvador R. G. Balestra, José M. Malagón, David Aparicio, Lucia Velasco, Asterios Charisiadis, Dooshaye Moonshiram, Margarita Darder, Pilar Aranda, Bernd Wicklein, Gustavo de Miguel, Javier Pérez‐Carvajal, Eva M. García‐Frutos   +13 more
wiley   +1 more source

RAGdeterm: Deterministic retrieval-augmented generation for code generation

SoftwareX
Large language models (LLMs) are increasingly used in software development, yet effective code generation requires reliable access to up-to-date project-specific source code. This paper introduces RAGdeterm, a deterministic Retrieval-Augmented Generation
A. Bochenek, J. Protasiewicz, W. Pedrycz
doaj   +1 more source