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.
This research explores Opportunities for neuromorphic computing algorithms and appl..., contributing new insights to the field of Artificial Intelligence.
AbstractThere is a failure mode in large language models that we do not have a good name for, and thatwe therefore tend not to treat seriously enough. We do not describe such a systemin detail here.
Vision-Language Pre-training (VLP) has advanced the performance for many vision-language tasks. BLIP also demonstrates strong generalization ability when directly transferred to video-language tasks i...
Nowadays, Industry 4.0 can be considered a reality, a paradigm integrating modern technologies and innovations. Then, we present an in-depth investigation of the main methods used in the literature: w...
Abstract Deep-learning models have become pervasive tools in science and engineering. Physics-aware training combines the scalability of backpropagation with the automatic mitigation of imperfections...
The last half decade has seen a steep rise in the number of contributions on safe learning methods for real-world robotic deployments from both the control and reinforcement learning communities. As d...
Combinatorial therapies have been recently proposed to improve the efficacy of anticancer treatment. These annotations will improve the interpretation of the mechanisms of action of drug combinations.
Optimization is an important and fundamental challenge to solve optimization problems in different scientific disciplines. The findings of POA are compared with eight well-known metaheuristic algorith...
This research explores Recent progress and future perspective on practical silicon..., contributing new insights to the field of Artificial Intelligence.
Abstract As basic research, it has also received increasing attention from people that the “curse of dimensionality” will lead to increase the cost of data storage and computing; it also influences th...
We present LaMDA: Language Models for Dialog Applications. We quantify factuality using a groundedness metric, and we find that our approach enables the model to generate responses grounded in known s...
Legged robots that can operate autonomously in remote and hazardous environments will greatly increase opportunities for exploration into underexplored areas. The result is a legged locomotion control...
This research explores SRDiff: Single image super-resolution with diffusion probabi..., contributing new insights to the field of Artificial Intelligence.
BACKGROUND: Heterogeneity in single-cell RNA-seq (scRNA-seq) data is driven by multiple sources, including biological variation in cellular state as well as technical variation introduced during exper...
Abstract Deep learning has been widely used for medical image segmentation and a large number of papers has been presented recording the success of deep learning in the field. For weakly supervised le...
The circular economy (CE) has the potential to capitalise upon emerging digital technologies, such as big data, artificial intelligence (AI), blockchain and the Internet of things (IoT), amongst other...
This chapter provides approaches to the problem of quantizing the numerical values in deep Neural Network computations, covering the advantages/disadvantages of current methods. Loosely related to NN...
Artificial intelligence can assist providers in a variety of patient care and intelligent health systems. Preferred reporting items for systematic reviews and Meta-Analysis guidelines are used to sele...
Modern computation based on the von Neumann architecture is today a mature cutting-edge science. The Roadmap is a collection of perspectives where leading researchers in the neuromorphic community pro...
This research explores Review the state-of-the-art technologies of semantic segment..., contributing new insights to the field of Artificial Intelligence.