Results 171 to 180 of about 250,954 (220)

READRetro web: A user-friendly platform for predicting plant natural product biosynthesis. [PDF]

Mol Cells
Kwak Y, Kim T, Kim SG, Park J.
europepmc   +1 more source

Effect of different exercise interventions on metabolic syndrome risk factors in postmenopausal women: a network meta-analysis. [PDF]

Front Physiol
Zhang T, Kabachkova AV, Deng Z, Liang Y, Li M, Yuan W.   +5 more
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Representativeness of a German AI-enabled data network for secondary epidemiological analysis based on electronic health records. [PDF]

PLoS One
Eichhorn S, Mitze FN, Wagner F, Seuthe IMC, Brinks R, Zimmermann A, Dastur M, Ladenbauer J, Park JJ.   +8 more
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Leveraging Retrieval-Augmented Large Language Models for Dietary Recommendations With Traditional Chinese Medicine's Medicine Food Homology: Algorithm Development and Validation.

JMIR Med Inform
Sha H, Gong F, Liu B, Liu R, Wang H, Wu T.   +5 more
europepmc   +1 more source

Retrieval-augmented generation elevates local LLM quality in radiology contrast media consultation. [PDF]

NPJ Digit Med
Wada A, Tanaka Y, Nishizawa M, Yamamoto A, Akashi T, Hagiwara A, Hayakawa Y, Kikuta J, Shimoji K, Sano K, Kamagata K, Nakanishi A, Aoki S.   +12 more
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Construction of intelligent decision support systems through integration of retrieval-augmented generation and knowledge graphs. [PDF]

Sci Rep
Wang S, Yang H, Bai G.
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RAGing ahead in rheumatology: new language model architectures to tame artificial intelligence. [PDF]

Ther Adv Musculoskelet Dis
Benavent D, Venerito V, Michelena X.
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Aggregating ranking methods for information retrieval: an overview

, 2007
Martin Veselý, Martin Rajman
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KeyBLD: Selecting Key Blocks with Local Pre-ranking for Long Document Information Retrieval

Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021
Transformer-based models, and especially pre-trained language models like BERT, have shown great success on a variety of Natural Language Processing and Information Retrieval tasks.
Minghan Li, Éric Gaussier
semanticscholar   +1 more source

Evaluating Generative Ad Hoc Information Retrieval

Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023
Recent advances in large language models have enabled the development of viable generative retrieval systems. Instead of a traditional document ranking, generative retrieval systems often directly return a grounded generated text as a response to a query.
Lukas Gienapp, Harrisen Scells, Niklas Deckers, Janek Bevendorff, Shuai Wang, Johannes Kiesel, S. Syed, Maik Frobe, Guide Zucoon, Benno Stein, Matthias Hagen, Martin Potthast   +11 more
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