45 citations · 49 across the 8 of their papers we have counts for
5 papers · 1 filter
MatTools: Benchmarking Large Language Models for Materials Science Tools
Siyu Liu, Bo Hu, Beilin Ye +3
Large language models (LLMs) are increasingly applied to materials science questions, including literature comprehension, property prediction, materials discovery and alloy design.…
Active Learning for Conditional Inverse Design with Crystal Generation and Foundation Atomic Models
Zhuoyuan Li, Siyu Liu, Beilin Ye +2
Artificial intelligence (AI) is transforming materials science, enabling both theoretical advancements and accelerated materials discovery. Recent progress in crystal generation mo…
Large Language Models for Material Property Predictions: elastic constant tensor prediction and materials design
Siyu Liu, Tongqi Wen, Beilin Ye +2
Efficient and accurate prediction of material properties is critical for advancing materials design and applications. The rapid-evolution of large language models (LLMs) presents a…
A Multi-agent Framework for Physical Laws Discovery
Bo Hu, Siyu Liu, Beilin Ye +6
Discovering explicit physical laws has traditionally depended on human intuition and domain expertise. Recent advances in artificial intelligence, particularly large language model…
A Prompt-Engineered Large Language Model, Deep Learning Workflow for Materials Classification
Siyu Liu, Tongqi Wen, A. S. L. Subrahmanyam Pattamatta +1
Large language models (LLMs) have demonstrated rapid progress across a wide array of domains. Owing to the very large number of parameters and training data in LLMs, these models i…