Results 91 to 100 of about 24,277 (306)
Advanced Intelligent Discovery, EarlyView.Large language models are transforming microbiome research by enabling advanced sequence profiling, functional prediction, and association mining across complex datasets. They automate microbial classification and disease‐state recognition, improving cross‐study integration and clinical diagnostics.
Jieqi Xing +4 more
wiley +1 more source
Frontiers in PsychiatryBackgroundRecently, there have been active proposals on how to utilize large language models (LLMs) in the fields of psychiatry and counseling. It would be interesting to develop programs with LLMs that generate psychodynamic assessments to help ...
Namwoo Kim +13 more
doaj +1 more source
, 2019 University of Minnesota M.A. thesis. November 2019. Major: Philosophy. Advisor: Peter Hanks. 1 computer file (PDF); vi, 83 pages.It can seem as if philosophy of perception has discussed hallucination almost more than perception itself.
Swanson, Link
core
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Advanced Intelligent Discovery, EarlyView.Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
Hallucinations in automated texts – A critical view on the emerging terminology
AI-LinguisticaThe term hallucination is used in AI discourse to describe AI-generated outputs that are unfounded and lack backing in input data, a phenomenon which occurs frequently enough for the academic community to shun widespread collaboration with AI writing ...
Annette Gerstenberg
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee +3 more
wiley +1 more source
Гуманитарные и юридические исследованияIntroduction. The relevance of the study lies primarily in the fact that the increasingly active appeal of the widest circles of users to the generation of texts of different genres, properties and volumes using the so-called LLM (Large Language Model ...
S. V. Gusarenko, M. K. Gusarenko
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Advanced Intelligent Discovery, EarlyView.This article establishes a Taguchi–Bayesian sampling strategy to reconstruct polymer processing–property landscape at minimal sampling cost, generically building the roadmap for materials database construction from sampling their vast design space. This sampling strategy is featured by an alternating lesson between uniformity and representativeness ...
Han Liu, Liantang Li
wiley +1 more source
Nursing process addressing the nursing focus “Hallucination”: A scoping review [PDF]
, 2019 Although hallucinations are prevalent in psychiatric disorders, such as psychosis or dementia, no studies were to be found in literature about the nursing process addressing the focus “Hallucination”.
Sampaio, Francisco Miguel Correia +6 more
core +1 more source
Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents
Advanced Intelligent Discovery, EarlyView.This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer +3 more
wiley +1 more source