Results 1 to 10 of about 89,115 (160)

Nursing Retrieval-Augmented Generation: Retrieval augmented generation for nursing question answering with large language models [PDF]

International Journal of Nursing Sciences
Objective: This study aimed to develop a Nursing Retrieval-Augmented Generation (NurRAG) system based on large language models (LLMs) and to evaluate its accuracy and clinical applicability in nursing question answering. Methods: A multidisciplinary team
Liping Xiong, Qiqiao Zeng, Weixiang Luo, Ronghui Liu   +3 more
doaj   +3 more sources

Medical LLMs: Fine-Tuning vs. Retrieval-Augmented Generation [PDF]

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   +2 more sources

Retrieval-Augmented Generation

Retrieval-augmented generation (RAG) is a hybrid architecture that combines the generative power of large language models (LLMs) with the factual reliability of information retrieval systems. Although the emergence of large language models (LLMs) has significantly improved the performance of natural language understanding and generation tasks. However,
Uday Kamath, Kevin Keenan, Garrett Somers, Sarah Sorenson   +3 more
  +7 more sources

Active Retrieval Augmented Generation

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
Despite the remarkable ability of large language models (LMs) to comprehend and generate language, they have a tendency to hallucinate and create factually inaccurate output. Augmenting LMs by retrieving information from external knowledge resources is one promising solution.
Jiang, Zhengbao, Xu, Frank F., Gao, Luyu, Sun, Zhiqing, Liu, Qian, Dwivedi-Yu, Jane, Yang, Yiming, Callan, Jamie, Neubig, Graham   +8 more
openaire   +2 more sources

Dynamic Retrieval-Augmented Generation

, 2023
Current state-of-the-art large language models are effective in generating high-quality text and encapsulating a broad spectrum of world knowledge. These models, however, often hallucinate and lack locally relevant factual data. Retrieval-augmented approaches were introduced to overcome these problems and provide more accurate responses. Typically, the
Shapkin, Anton, Litvinov, Denis, Zharov, Yaroslav, Bogomolov, Egor, Galimzyanov, Timur, Bryksin, Timofey   +5 more
openaire   +2 more sources

RACE: Retrieval-augmented Commit Message Generation

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022
Commit messages are important for software development and maintenance. Many neural network-based approaches have been proposed and shown promising results on automatic commit message generation. However, the generated commit messages could be repetitive or redundant.
Shi, Ensheng, Wang, Yanlin, Tao, Wei, Du, Lun, Zhang, Hongyu, Han, Shi, Zhang, Dongmei, Sun, Hongbin   +7 more
openaire   +2 more sources

Meetings and Meeting Modeling in Smart Environments [PDF]

, 2006
In this paper we survey our research on smart meeting rooms and its relevance for augmented reality meeting support and virtual reality generation of meetings in real time or off-line.
Akker, Rieks op den, Heylen, Dirk, Nijholt, Anton   +2 more
core   +4 more sources

DF-RAG:A Retrieval-augmented Generation Method Based on Query Rewriting and Knowledge Selection [PDF]

Jisuanji kexue
Large language models have demonstrated formidable comprehension abilities in conversational tasks,yet they still face issues such as data timeliness and inefficiency in handling specific knowledge.To address these challenges,Retrieval-augmented ...
ZHANG Haoran, HAO Wenning, JIN Dawei, CHENG Kai, ZHAI Ying
doaj   +1 more source

Augmenting human memory using personal lifelogs [PDF]

, 2010
Memory is a key human facility to support life activities, including social interactions, life management and problem solving. Unfortunately, our memory is not perfect.
Byrne D., Kelly L., Lamming M., Schacter D. L.   +3 more
core   +1 more source

Towards the improvement of augmentative and alternative communication through the modelling of conversation [PDF]

, 2013
Non-speaking people who use Augmentative and Alternative Communication (AAC) systems typically have low rates of communication which reduces their ability to interact with others.
Alm, Norman, Arnott, John L.
core   +3 more sources