Recently, there has been growing interest in developing the next-generation recommender
systems (RSs) based on pretrained large language models (LLMs). However, the semantic …

In existing graph data, the connection relationships often exhibit uniform weights, leading to
the model aggregating neighboring nodes with equal weights across various connection …

Abstract Large Language Models (LLMs) have taken the field of AI by storm, but their
adoption in the field of Artificial Life (ALife) has been, so far, relatively reserved. In this work …

Data-driven methods in materials science typically suffer from a lack of experimentally
collected training data. Although various transfer learning methods on calculated crystal …

Automated materials synthesis requires historical data, but extracting detailed data and
metadata from publications is challenging. We developed initial strategies for using large …

In condensed matter physics and materials science, predicting material properties
necessitates understanding intricate many-body interactions. Conventional methods such as …