This study presents domain-adapted language models for optoelectronics, enhancing NLP tasks like classification and ...

In today's data-driven environment, Python has become the mainstream language in the fields of machine learning and data science due to its concise syntax, rich library support, and active community, ...

Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL) fine-tuning are two common methods for post-training large models. While reinforcement learning fine-tuning has made significant progress ...

Recent advances in high-throughput microbiome profiling have generated expansive data sets that offer unprecedented ...

Abstract: This study proposes an image-text multimodal classification algorithm based on a combination of convolutional neural networks (CNN) and Transformer, aiming to solve the key problems in ...

Two projects from the Arab World exemplify the potential of AI-driven approaches to disaster response and displacement monitoring.

An AI-powered standard legal language framework could create a common foundation for legal communication that may restructure ...