1 citations · 2 across the 5 of their papers we have counts for
9 papers
Bioinfoysis Technical Report
Qingyang Shao, Xin Zhang, Zhouyang Yuan +25
Large language model agents have shown promise in bioinformatics, but most existing systems focus primarily on producing final answers, treating planning, tool use, and code execut…
Harnessing agent memory to build lifelong AI partners for materials scientists
Siyu Liu, Bo Hu, Beilin Ye +3
Materials research advances through accumulated experience - scripts that work, protocols that are trusted, warnings attached to failed calculations or experiments, and judgement t…
Mozi: Governed Autonomy for Drug Discovery LLM Agents
He Cao, Siyu Liu, Fan Zhang +7
Tool-augmented large language model (LLM) agents promise to unify scientific reasoning with computation, yet their deployment in high-stakes domains like drug discovery is bottlene…
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…