Siyu Yuan (员司雨) is a third-year Ph.D. student at Fudan University. She is devoted to making machines have human-like cognitive abilities and aligning autonomous generative agents with human cognition. Her research topics are mostly around cognitive science with generative agents, including (but not limited to)
(Download my resumé. The last update was on 2024-05.)
Ph.D., Statistics, 2021-2026 (estimated)
Fudan University
B.S., Bachelor of Data Science and big data technology, 2017-2021
Fudan University
We propose a million-scale analogy knowledge base derived from existing knowledge graphs to enhance the analogical reasoning capabilities of LMs.
EASYTOOL is a framework designed to enhance the ability of LLM-based agents to use tools by simplifying and standardizing tool documentation.
We propose the analogical structure abduction task with a benchmark of scientific analogical reasoning with structure abduction to evaluate LLMs from a cognitive perspective to align with humans.