Zobrazeno 1 - 10
of 902
pro vyhledávání: '"Pan Qian"'
Publikováno v:
Microsystems & Nanoengineering, Vol 10, Iss 1, Pp 1-10 (2024)
Abstract In this paper, a composite pressure-sensitive mechanism combining diaphragm bending and volume compression was developed for resonant pressure microsensors to achieve high-pressure measurements with excellent accuracy. The composite mechanis
Externí odkaz:
https://doaj.org/article/3beeefb5108044f3bb93cf44f299e31c
Publikováno v:
Frontiers in Psychology, Vol 15 (2024)
BackgroundThe transition to parenthood, which is influenced a lot by local parenting culture, is a dramatic stress for both men and women. Chinese social and cultural contexts form specific parental culture, shaping the unique experience of transitio
Externí odkaz:
https://doaj.org/article/d73ac8b9ff8c4059b9e420ceaa38ac81
Publikováno v:
BMC Pregnancy and Childbirth, Vol 23, Iss 1, Pp 1-11 (2023)
Abstract Background Gestational diabetes mellitus (GDM) threatens GDM mothers and their offspring’s health and breastfeeding is one of the most effective ways to decrease the risk. However, the prevalence of breastfeeding among GDM mothers is far f
Externí odkaz:
https://doaj.org/article/1b17572ffe9f4c6dbd4928fac698d4ab
Autor:
Padhi, Inkit, Nagireddy, Manish, Cornacchia, Giandomenico, Chaudhury, Subhajit, Pedapati, Tejaswini, Dognin, Pierre, Murugesan, Keerthiram, Miehling, Erik, Cooper, Martín Santillán, Fraser, Kieran, Zizzo, Giulio, Hameed, Muhammad Zaid, Purcell, Mark, Desmond, Michael, Pan, Qian, Ashktorab, Zahra, Vejsbjerg, Inge, Daly, Elizabeth M., Hind, Michael, Geyer, Werner, Rawat, Ambrish, Varshney, Kush R., Sattigeri, Prasanna
We introduce the Granite Guardian models, a suite of safeguards designed to provide risk detection for prompts and responses, enabling safe and responsible use in combination with any large language model (LLM). These models offer comprehensive cover
Externí odkaz:
http://arxiv.org/abs/2412.07724
Publikováno v:
Frontiers in Public Health, Vol 10 (2022)
BackgroundThe public's irrational use of antibiotics for upper respiratory tract infections (URTIs) is prevalent worldwide. This study aims to synthesize evidence on how people use antibiotics to treat URTIs, its prevalence and determinants.MethodsA
Externí odkaz:
https://doaj.org/article/49653c9e50074464879914f601d8431c
Publikováno v:
Frontiers in Endocrinology, Vol 13 (2022)
BackgroundGestational diabetes mellitus (GDM) is a condition in which women develop hyperglycemia during pregnancy, and is associated with long-term health burden on both mother and their offspring, such as future type 2 diabetes mellitus (T2DM). Alt
Externí odkaz:
https://doaj.org/article/200e8c48f67e45728814bc1654081435
Publikováno v:
IEEE Access, Vol 9, Pp 45853-45863 (2021)
Image deblurring aims to restore the latent sharp image from the blurred one. In recent years, some learning-based image deblurring methods have achieved significant advances. However, the tradeoff between the texture details and model parameters is
Externí odkaz:
https://doaj.org/article/9b27928a7a544332a58c78db7f60ca06
Autor:
Wagner, Nico, Desmond, Michael, Nair, Rahul, Ashktorab, Zahra, Daly, Elizabeth M., Pan, Qian, Cooper, Martín Santillán, Johnson, James M., Geyer, Werner
LLM-as-a-Judge is a widely used method for evaluating the performance of Large Language Models (LLMs) across various tasks. We address the challenge of quantifying the uncertainty of LLM-as-a-Judge evaluations. While uncertainty quantification has be
Externí odkaz:
http://arxiv.org/abs/2410.11594
Autor:
Ashktorab, Zahra, Desmond, Michael, Pan, Qian, Johnson, James M., Cooper, Martin Santillan, Daly, Elizabeth M., Nair, Rahul, Pedapati, Tejaswini, Achintalwar, Swapnaja, Geyer, Werner
Evaluation of large language model (LLM) outputs requires users to make critical judgments about the best outputs across various configurations. This process is costly and takes time given the large amounts of data. LLMs are increasingly used as eval
Externí odkaz:
http://arxiv.org/abs/2410.00873
Autor:
Ashktorab, Zahra, Pan, Qian, Geyer, Werner, Desmond, Michael, Danilevsky, Marina, Johnson, James M., Dugan, Casey, Bachman, Michelle
In this paper, we investigate the impact of hallucinations and cognitive forcing functions in human-AI collaborative text generation tasks, focusing on the use of Large Language Models (LLMs) to assist in generating high-quality conversational data.
Externí odkaz:
http://arxiv.org/abs/2409.08937