Results 141 to 150 of about 81,815 (304)

Agglomeration within and between regions: Two econometric based indicators [PDF]

We propose two indexes to measure the agglomeration forces acting within and between different regions. Unlike the existing measures of agglomeration, our model-based indexes allow for simultaneous treatment of both aspects.
Marcello Pagnini, Valter Di Giacinto
core  

Advanced Experiment Design Strategies for Drug Development

Advanced Intelligent Discovery, EarlyView.
Wang et al. analyze 592 drug development studies published between 2020 and 2024 that applied design of experiments methodologies. The review surveys both classical and emerging approaches—including Bayesian optimization and active learning—and identifies a critical gap between advanced experimental strategies and their practical adoption in ...
Fanjin Wang, Anthony Harker, Mohan Edirisinghe, Maryam Parhizkar   +3 more
wiley   +1 more source

Evaluating LLMs for visualization generation and understanding

Discover Data
Information Visualization has been utilized to gain insights from complex data. In recent times, Large Language models (LLMs) have performed very well in many tasks.
Saadiq Rauf Khan, Vinit Chandak, Sougata Mukherjea   +2 more
doaj   +1 more source

Low participation and regional inequalities : interrelated features of the Hungarian labour market. Case study [PDF]

"Low participation and spatial polarisation are two interrelated features of the Hungarian labour market. The paper investigates these features taking stock of stylised facts and results of the relevant empirical literature.
Fazekas, Karoly
core  

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

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, Hyeonbin Moon, Junhyeong Lee, Seunghwa Ryu   +3 more
wiley   +1 more source

Assessing clinical medicine students’ acceptance of large language model: based on technology acceptance model

BMC Medical Education
While large language models (LLMs) have demonstrated significant potential in medical education, there is limited understanding of medical students’ acceptance of LLMs and the factors influencing their use.
Fuze Liu, Xiao Chang, Qi Zhu, Yue Huang, Yifei Li, Hai Wang   +5 more
doaj   +1 more source

Teacher supply and the market for teachers [PDF]

The share of non-certified teachers in Swedish compulsory public schools has grown considerably during the last decade, from 7.2 percent in 1995/96 to 17.2 percent in 2003/04.
Andersson, Christian, Waldenström, Nina
core  

LLMStinger: Jailbreaking LLMs using RL fine-tuned LLMs

We introduce LLMStinger, a novel approach that leverages Large Language Models (LLMs) to automatically generate adversarial suffixes for jailbreak attacks. Unlike traditional methods, which require complex prompt engineering or white-box access, LLMStinger uses a reinforcement learning (RL) loop to fine-tune an attacker LLM, generating new suffixes ...
Jha, Piyush, Arora, Arnav, Ganesh, Vijay
openaire   +2 more sources

Machine Learning‐Assisted Second‐Order Perturbation Theory for Chemical Potential Correction Toward Hubbard U Determination

Advanced Intelligent Discovery, EarlyView.
In this work, the Doubao large language model (LLM) is involved in the formula derivation processes for Hubbard U determination regarding the second‐order perturbations of the chemical potential. The core ML tool is optimized for physical domain knowledge, which is not limited to parameter prediction but rather serves as an interactive physical theory ...
Mingzi Sun, Tong Wu, Baian Chen, Zikang Li, Qiuyang Lu, Lu Lu, Hon Ho Wong, Cheuk Hei Chan, Bolong Huang   +8 more
wiley   +1 more source

Exploring the potential of large language models for integration into an academic statistical consulting service-the EXPOLS study protocol.

PLoS ONE
BackgroundThe advancement of Artificial Intelligence, particularly Large Language Models (LLMs), is rapidly progressing. LLMs, such as OpenAI's GPT, are becoming vital in scientific and medical processes, including text production, knowledge synthesis ...
Urs Alexander Fichtner, Jochen Knaus, Erika Graf, Georg Koch, Jörg Sahlmann, Dominikus Stelzer, Martin Wolkewitz, Harald Binder, Susanne Weber   +8 more
doaj   +1 more source