Results 91 to 100 of about 3,238,639 (146)

An explainable graph retrieval augmented generation framework for personalized nutrition recommendation. [PDF]

Front Artif Intell
Dindukurthi V, Jain D, Tripathi A, Obbineni JM, Kandasamy I.   +4 more
europepmc   +1 more source

Evaluation of a Retrieval-Augmented Generation-Based Large Language Model for Evidence-Based Herb and Supplement Information in Cancer Care. [PDF]

JMIR Cancer
Hou YN, Gubili J, Jain P, Lam CS, Chatterjee A, Mao JJ.   +5 more
europepmc   +1 more source

Robust retrieval augmented generation

Retrieval Augmented Generation (RAG) enhances Large Language Models with external knowledge but is vulnerable to noisy and contradictory retrieved content.
Hoh, Shu Hao
core  

Fine-Tuning, Retrieval-Augmented Generation, and Hybrid Adaptation of Language Models for Clinical Decision-Making in Health Care: Systematic Review. [PDF]

J Med Internet Res
Patel A, Khand Y, Vallamchetla SK, Li P, Tao C, Cheung J.   +5 more
europepmc   +1 more source

Evaluating large language model clinical reasoning in glaucoma using retrieval-augmented generation. [PDF]

Adv Ophthalmol Pract Res
Yin H, Miao Q, Zhou W, Hu C, Guo Y, Shen L, Cai H, Grzybowski A, Jin K.   +8 more
europepmc   +1 more source

MMCRAG-Resp: a multi-modal corrective retrieval-augmented generation framework for explainable respiratory disease reasoning. [PDF]

Front Artif Intell
Anny Leema A, Rajashri S, Sriram M, Girish M, Balakrishnan P.   +4 more
europepmc   +1 more source

Feasibility of retrieval-augmented generation for large language models with Japanese input in radiotherapy. [PDF]

J Radiat Res
Takahashi Y, Kadoya N, Arai K, Tanno H, Tanaka S, Katsuta Y, Hoshino T, Harada H, Omata S, Yamamoto T, Umezawa R, Yasui K, Hayashi N, Jingu K.   +13 more
europepmc   +1 more source

Fine-Tuning, Retrieval-Augmented Generation, and Hybrid Large Language Models for Postoperative Decision Support: Comparative Analysis. [PDF]

J Med Internet Res
Prabha S, Collaco BG, Gomez-Cabello CA, Haider SA, Genovese A, Fang Z, Wood N, Bagaria S, Tao C, Forte AJ.   +9 more
europepmc   +1 more source

Seven Failure Points When Engineering a Retrieval Augmented Generation System

Seven Failure Points When Engineering a Retrieval Augmented Generation ...
Zach Brannelly (18826309), Stefanus Kurniawan (13079919), Srikanth Thudumu (13096272), Scott Barnett (13060245), Mohamed Abdelrazek (13082583)   +4 more
core  

RAGVA: Engineering retrieval augmented generation-based virtual assistants in practice

RAGVA: Engineering retrieval augmented generation-based virtual assistants in ...
M Fu (9883688), L Vandenhurk (21006575), C Tantithamthavorn (21006572), R Yang (6699815), Chetan Arora (13063929), J Chua (9876659)   +5 more
core