Results 231 to 240 of about 1,137,884 (305)

Retrieval-Augmented Language Models Enable Scalable Chemical Source Classification in Metabolomics Workflows. [PDF]

open access: yesAnal Chem
Rajkumar P   +12 more
europepmc   +1 more source

Learning to Prompt for Vision-Language Models

International Journal of Computer Vision, 2021
Large pre-trained vision-language models like CLIP have shown great potential in learning representations that are transferable across a wide range of downstream tasks.
Kaiyang Zhou   +3 more
semanticscholar   +1 more source

Prompt engineering in consistency and reliability with the evidence-based guideline for LLMs

open access: yesNpj Digital Medicine
The use of large language models (LLMs) in clinical medicine is currently thriving. Effectively transferring LLMs’ pertinent theoretical knowledge from computer science to their application in clinical medicine is crucial.

exaly   +2 more sources

AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection

International Conference on Learning Representations, 2023
Zero-shot anomaly detection (ZSAD) requires detection models trained using auxiliary data to detect anomalies without any training sample in a target dataset.
Qihang Zhou   +4 more
semanticscholar   +1 more source

AI literacy and its implications for prompt engineering strategies

open access: yesComputers and Education Artificial Intelligence
Artificial intelligence technologies are rapidly advancing. As part of this development, large language models (LLMs) are increasingly being used when humans interact with systems based on artificial intelligence (AI), posing both new opportunities and ...
Andreas Janson
exaly   +2 more sources

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