collaborators

8 papers

cs.LG2026

Towards Diverse Scientific Hypothesis Search with Large Language Models

Haorui Wang, Parshin Shojaee, Kazem Meidani +7

Large language models (LLMs) are on the rise for accelerating scientific discovery, most recently in advanced tasks such as generating valid scientific hypotheses. Yet in many disc…

cs.AI2026

LLM-Augmented Chemical Synthesis and Design Decision Programs

Haorui Wang, Jeff Guo, Lingkai Kong +4

Retrosynthesis, the process of breaking down a target molecule into simpler precursors through a series of valid reactions, stands at the core of organic chemistry and drug develop…

cs.AI2026

Evaluating Large Language Models in Scientific Discovery

Zhangde Song, Jieyu Lu, Yuanqi Du +53

Large language models (LLMs) are increasingly applied to scientific research, yet prevailing science benchmarks probe decontextualized knowledge and overlook the iterative reasonin…

cs.AI2026

Accelerating Scientific Discovery with Autonomous Goal-evolving Agents

Yuanqi Du, Botao Yu, Tianyu Liu +25

There has been unprecedented interest in developing agents that expand the boundary of scientific discovery, primarily by optimizing quantitative objective functions specified by s…

cs.LG2025

Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints

Lingkai Kong, Yuanqi Du, Wenhao Mu +8

Addressing real-world optimization problems becomes particularly challenging when analytic objective functions or constraints are unavailable. While numerous studies have addressed…

cond-mat.mtrl-sci2025

MatLLMSearch: Crystal Structure Discovery with Evolution-Guided Large Language Models

Jingru Gan, Peichen Zhong, Yuanqi Du +7

Crystal structure generation is fundamental to materials science, enabling the discovery of novel materials with desired properties. While existing approaches leverage Large Langua…