Large language models (LLMs) have demonstrated the ability to generate generic computer programs, providing an understanding of program structure. However, it is challenging to find the true capabilities of LLMs, especially in finding tasks they did not see during training. It is crucial to find whether LLMs can truly “understand” the symbolic graphics programs, which… →
The application of RL to problems in complex decision-making, particularly in situations with limited resources and uncertain outcomes, has recently become very useful. In the varied applications of RL, what distinguishes Restless Multi-Arm Bandits (RMABs) is their solution to multi-agent resource allocation problems. RMAB models depict the management of several decision points or “arms,” each… →
The multi-scale difficulty of designing new alloys calls for a comprehensive strategy, as this procedure includes gathering pertinent information, using advanced computational methods, running experimental validations, and carefully examining the results. Because the tasks involved in this complex workflow are intricate, it has traditionally taken a lot of time and was mostly completed by human… →
Hardware manufacturers must follow rules and regulations called “hardware safety compliance” to ensure their goods aren’t harmful to people or the environment. Typical areas covered by these rules include product design, production, testing, and labeling, though they differ by country and sector. The existing approaches to ensuring hardware safety compliance have several things that could… →
Accurately modeling nonlinear dynamical systems using observable data remains a significant challenge across various fields such as fluid dynamics, climate science, and mechanical engineering. Traditional linear approximation methods often fall short in capturing the complex behaviors exhibited by these systems, leading to inaccurate predictions and ineffective control strategies. Addressing this challenge is crucial for advancing… →
The evaluation of legal knowledge in large language models (LLMs) has primarily focused on English-language contexts, with benchmarks like MMLU and LegalBench providing foundational methodologies. However, the assessment of Arabic legal knowledge remained a significant gap. Previous efforts involved translating English legal datasets and utilizing limited Arabic legal documents, highlighting the need for dedicated Arabic… →
Accurate assessment of vital parameters is essential for diagnosis and triage of critically ill patients, but not always feasible in out-of-hospital settings due to the lack of suitable devices. We performed an extensive validation of a novel prototype in-ear device, which was proposed for the non-invasive, combined measurement of core body temperature (Tc), oxygen saturation… →
Deep learning models typically represent knowledge statically, making adapting to evolving data needs and concepts challenging. This rigidity necessitates frequent retraining or fine-tuning to incorporate new information, which could be more practical. The research paper “Towards Flexible Perception with Visual Memory” by Geirhos et al. presents an innovative solution that integrates the symbolic strength of… →