Explore the latest peer-reviewed research with AI-generated summaries, key findings, and insights for easy understanding. All content is legally sourced from academic metadata with links to original papers.
Abstract This study provides an overview of research on teachers’ use of artificial intelligence (AI) applications and machine learning methods to analyze teachers’ data. These roles include acting as...
There is a growing consensus that solutions to complex science and engineering problems require novel methodologies that are able to integrate traditional physics-based modeling approaches with advanc...
This research explores Unlocking the value of artificial intelligence in human reso..., contributing new insights to the field of Artificial Intelligence.
Chain-of-thought prompting combined with pre-trained large language models has achieved encouraging results on complex reasoning tasks. Self-consistency leverages the intuition that a complex reasonin...
This research explores Gradient-enhanced physics-informed neural networks for forwa..., contributing new insights to the field of Artificial Intelligence.
Transformers have recently lead to encouraging progress in computer vision. We hope this work will facilitate advanced transformer research in computer vision.
Humans can naturally and effectively find salient regions in complex scenes. In this survey, we provide a comprehensive review of various attention mechanisms in computer vision and categorize them ac...
Topic models can be useful tools to discover latent topics in collections of documents. More specifically, BERTopic generates document embedding with pre-trained transformer-based language models, clu...
This research explores Museum of spatial transcriptomics, contributing new insights to the field of Artificial Intelligence.
Identification of cell populations often relies on manual annotation of cell clusters using established marker genes. We also demonstrate how ScType distinguishes between healthy and malignant cell po...
This research explores survey of modern deep learning based object detection models, contributing new insights to the field of Artificial Intelligence.
Abstract Version 5.0 of the ORCA quantum chemistry program suite was released in July 2021. The article describes the most salient features of the program.
Deep learning has achieved remarkable success in numerous domains with help from large amounts of big data. Subsequently, we perform an in-depth analysis of noise rate estimation and summarize the typ...
We present DINO (\textbf{D}ETR with \textbf{I}mproved de\textbf{N}oising anch\textbf{O}r boxes), a advanced end-to-end object detector. Compared to other models on the leaderboard, DINO significantly...
This research explores Data-driven probabilistic machine learning in sustainable sm..., contributing new insights to the field of Artificial Intelligence.
This research explores AI for next generation computing: Emerging trends and future..., contributing new insights to the field of Artificial Intelligence.
Making language models bigger does not inherently make them better at following a user's intent. Moreover, InstructGPT models show improvements in truthfulness and reductions in toxic output generatio...
This research explores Molecular contrastive learning of representations via graph..., contributing new insights to the field of Artificial Intelligence.
Abstract Educational data mining has become an effective tool for exploring the hidden relationships in educational data and predicting students' academic achievements. Such data-driven studies are ve...
The success of monocular depth estimation relies on large and diverse training sets. The experiments confirm that mixing data from complementary sources greatly improves monocular depth estimation.