1 citations · 1 across the 3 of their papers we have counts for
5 papers
BuildBench: Benchmarking LLM Agents on Compiling Real-World Open-Source Software
Zehua Zhang, Ati Priya Bajaj, Divij Handa +13
Automatically compiling open-source software (OSS) projects is a vital, labor-intensive, and complex task, which makes it a good challenge for LLM Agents. Existing methods rely on…
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…