Results 71 to 80 of about 14,626 (158)

Document Retrieval Augmented Fine-Tuning (DRAFT) for Safety-Critical Software Assessment

IEEE Access
The evaluation of safety critical software requires a robust evaluation against complex regulatory frameworks, a process traditionally limited by manual evaluation.
Regan Bolton, Mohammadreza Sheikhfathollahi, Simon Parkinson, Vanessa Vulovic, Gary Bamford, Dan Basher, Howard Parkinson   +6 more
doaj   +1 more source

GRAG: Graph Retrieval-Augmented Generation

Findings of the Association for Computational Linguistics: NAACL 2025
Naive Retrieval-Augmented Generation (RAG) focuses on individual documents during retrieval and, as a result, falls short in handling networked documents which are very popular in many applications such as citation graphs, social media, and knowledge graphs.
Yuntong Hu, Zhihan Lei, Zheng Zhang 0047, Bo Pan 0009, Chen Ling 0003, Liang Zhao 0002   +5 more
openaire   +2 more sources

Case Study on Understanding the Power of Retrieval Augmented Generation (RAG) [PDF]

Journal of Systemics, Cybernetics and Informatics
This paper explores how Generative AI is changing with the use of Retrieval-Augmented Generation (RAG). RAG helps improve Artificial Intelligence (AI) systems by making them more capable, efficient and accurate.
Venkata Jaipal Reddy Batthula, Richard S. Segall, Sreejith Sivasubramony   +2 more
doaj  

An Empirical Evaluation of Retrieval, Reranking, and Similarity for a Q&A-Based Retrieval Augmented Generation System

IEEE Access
Retrieval-Augmented Generation (RAG) has emerged as a fundamental paradigm for improving Large Language Models (LLMs) by incorporating external knowledge retrieval.
Harun Elkiran, Jawad Rasheed
doaj   +1 more source

Differentially Private Retrieval-Augmented Generation

CoRR
Retrieval-augmented generation (RAG) is a widely used framework for reducing hallucinations in large language models (LLMs) on domain-specific tasks by retrieving relevant documents from a database to support accurate responses. However, when the database contains sensitive corpora, such as medical records or legal documents, RAG poses serious privacy ...
Tingting Tang, James Flemings, Yongqin Wang, Murali Annavaram   +3 more
openaire   +2 more sources

A Survey of Multimodal Retrieval-Augmented Generation

CoRR
Multimodal Retrieval-Augmented Generation (MRAG) enhances large language models (LLMs) by integrating multimodal data (text, images, videos) into retrieval and generation processes, overcoming the limitations of text-only Retrieval-Augmented Generation (RAG). While RAG improves response accuracy by incorporating external textual knowledge, MRAG extends
Lang Mei, Siyu Mo, Zhihan Yang, Chong Chen 0001   +3 more
openaire   +2 more sources

Retrieval Augmented Generation Data Query Technique for Pineapple Cultivation

Journal of Engineering and Sustainable Development
Generative artificial intelligence is advancing at a blistering pace. Large Language Models, in particular, have sped up the development of machine learning applications.
Badril Abu Bakar, Siti Noor Aliah Baharom, Mohd Taufik Ahmad, Mohd Nizam Zubir, Adli Fikri Ahmad Sayuti, Mohd Aufa Mhd Bookeri   +5 more
doaj   +1 more source

Retrieval Augmented Generation for Historical Newspapers

Proceedings of the 24th ACM/IEEE Joint Conference on Digital Libraries
Nowadays, the accessibility and long-term preservation of historical records are significantly impacted by the sharp increase in the digitization of these archives. This shift creates new opportunities for researchers and students in multiple disciplines to broaden their knowledge or conduct multidisciplinary research. However, given the vast amount of
The-Trung Tran, Carlos-Emiliano González-Gallardo, Antoine Doucet   +2 more
openaire   +2 more sources

Molecule Generation with Fragment Retrieval Augmentation

Advances in Neural Information Processing Systems 37
Fragment-based drug discovery, in which molecular fragments are assembled into new molecules with desirable biochemical properties, has achieved great success. However, many fragment-based molecule generation methods show limited exploration beyond the existing fragments in the database as they only reassemble or slightly modify the given ones.
Seul Lee, Karsten Kreis, Srimukh Prasad Veccham, Meng Liu 0015, Danny Reidenbach, Saee Paliwal 0001, Arash Vahdat, Weili Nie   +7 more
openaire   +3 more sources

Question Answering Enhancement Method for Large Educational Models Based on Re-ranking and Post-retrieval Reflection

大数据
Computer education is one of the requirements of modern information society education. With the development of large language models, there has been increasing attention on applying these models to the computer education process.
SUN Haoran, WANG Zhihao, WU Yifan, XIANG Yang   +3 more
doaj