Zobrazeno 1 - 10
of 5 854
pro vyhledávání: '"Rosenman, A."'
Autor:
Stan, Gabriela Ben-Melech, Aflalo, Estelle, Luo, Man, Rosenman, Shachar, Le, Tiep, Paul, Sayak, Tseng, Shao-Yen, Lal, Vasudev
While Large Vision Language Models (LVLMs) have become masterly capable in reasoning over human prompts and visual inputs, they are still prone to producing responses that contain misinformation. Identifying incorrect responses that are not grounded
Externí odkaz:
http://arxiv.org/abs/2412.01487
Autor:
Choubey, Prafulla Kumar, Su, Xin, Luo, Man, Peng, Xiangyu, Xiong, Caiming, Le, Tiep, Rosenman, Shachar, Lal, Vasudev, Mui, Phil, Ho, Ricky, Howard, Phillip, Wu, Chien-Sheng
Knowledge graphs (KGs) generated by large language models (LLMs) are becoming increasingly valuable for Retrieval-Augmented Generation (RAG) applications that require knowledge-intensive reasoning. However, existing KG extraction methods predominantl
Externí odkaz:
http://arxiv.org/abs/2410.16597
We employ a Large Language Model (LLM) to convert unstructured psychological interviews into structured questionnaires spanning various psychiatric and personality domains. The LLM is prompted to answer these questionnaires by impersonating the inter
Externí odkaz:
http://arxiv.org/abs/2406.06636
Despite impressive recent advances in text-to-image diffusion models, obtaining high-quality images often requires prompt engineering by humans who have developed expertise in using them. In this work, we present NeuroPrompts, an adaptive framework t
Externí odkaz:
http://arxiv.org/abs/2311.12229
Autor:
Sarah E. Wiehe, Tammie L. Nelson, Bridget Hawryluk, Unai Miguel Andres, Matthew C. Aalsma, Marc B. Rosenman, Michael S. Butler, Michelle Harris, Kem Moore, C. Dana Scott, Sami Gharbi, Lisa Parks, Dustin Lynch, Ross D. Silverman, J. Dennis Fortenberry
Publikováno v:
Research Involvement and Engagement, Vol 10, Iss 1, Pp 1-17 (2024)
Abstract Background Though social determinants are the primary drivers of health, few studies of people living with HIV focus on non-clinical correlates of insecure and/or fragmented connections with the care system. Our team uses linked clinical and
Externí odkaz:
https://doaj.org/article/8d2a1a521b3b40bb84c062f7b16fbd46
Motivated by the proliferation of observational datasets and the need to integrate non-randomized evidence with randomized controlled trials, causal inference researchers have recently proposed several new methodologies for combining biased and unbia
Externí odkaz:
http://arxiv.org/abs/2309.06727
Autor:
Xu, Xiao, Li, Bei, Wu, Chenfei, Tseng, Shao-Yen, Bhiwandiwalla, Anahita, Rosenman, Shachar, Lal, Vasudev, Che, Wanxiang, Duan, Nan
Two-Tower Vision-Language (VL) models have shown promising improvements on various downstream VL tasks. Although the most advanced work improves performance by building bridges between encoders, it suffers from ineffective layer-by-layer utilization
Externí odkaz:
http://arxiv.org/abs/2306.00103
Autor:
Wang, Shuxian, Zhang, Yubo, McGill, Sarah K., Rosenman, Julian G., Frahm, Jan-Michael, Sengupta, Soumyadip, Pizer, Stephen M.
Reconstructing a 3D surface from colonoscopy video is challenging due to illumination and reflectivity variation in the video frame that can cause defective shape predictions. Aiming to overcome this challenge, we utilize the characteristics of surfa
Externí odkaz:
http://arxiv.org/abs/2303.07264
Autor:
Abigail M. Gauen, Yaojie Wang, Amanda M. Perak, Matthew M. Davis, Marc Rosenman, Donald M. Lloyd‐Jones, Rachel Zmora, Norrina B. Allen, Lucia C. Petito
Publikováno v:
Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, Vol 13, Iss 21 (2024)
Background Preventive screenings in children encourage maintenance of optimal cardiovascular health, but gaps may exist between recommendations and clinical practice. We evaluated adherence to pediatric guidelines for universal age‐based and risk
Externí odkaz:
https://doaj.org/article/abd825c894744e0fb8fbbea1c7b2f470
Autor:
Kenny, Christopher T., Kuriwaki, Shiro, McCartan, Cory, Rosenman, Evan T. R., Simko, Tyler, Imai, Kosuke
Publikováno v:
Harvard Data Science Review, (Special Issue 2, 2023)
In "Differential Perspectives: Epistemic Disconnects Surrounding the US Census Bureau's Use of Differential Privacy," boyd and Sarathy argue that empirical evaluations of the Census Disclosure Avoidance System (DAS), including our published analysis,
Externí odkaz:
http://arxiv.org/abs/2210.08383