Computational science

Summary of the RBB-LLM Framework Methodology The RBB-LLM framework comprises three key components: peer review document collection and filtering, reflection bank construction, and LLM-assisted reasoning....

Recent studies explore the intersection of natural language processing (NLP) and mental health, focusing on early maladaptive schemas and depression detection. Gollapalli et al....

In this content, we define the density of large language models (LLMs) as the ratio of effective parameter size to actual parameter size. We...

Unlocking AI's Role in Scientific Research: Join the Revolution! AI is reshaping every phase of scientific inquiry, from hypothesis generation to manuscript writing. Yet, most...

Explore Innovations in AI Hardware! Uncover the groundbreaking advancements of our optical experimental setup capable of matrix-vector multiplication. This innovative technology blends optics and electronics...

ToM tasks evaluate the capacity of Language Models (LLMs) in understanding others' mental states. Central to this assessment are false-belief tasks (FB), particularly unexpected...

The study evaluates a novel GAN-based educational system's output quality and responsiveness compared to four baseline architectures—Baseline-GAN, StyleGAN, Pix2Pix, and CycleGAN. Using Fréchet Inception...

Unlocking the Future of Scientific Research with AI AI is revolutionizing the landscape of scientific inquiry, driving progress from hypothesis generation to manuscript...