From the 2 of 39 linked papers with an AI index.
18 citations · 25 across the 14 of their papers we have counts for
10 papers · 1 filter
Agentic generation of verifiable rules for deterministic, self-expanding reaction classification
Daniel Armstrong, Maarten Dobbelaere, Valentas Olikauskas +4
The paper introduces an automated system where multiple large language models classify chemical reactions and generate verifiable reaction rules, expanding a reaction taxonomy from…
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…
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…
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…
CASCADE: Cumulative Agentic Skill Creation through Autonomous Development and Evolution
Xu Huang, Junwu Chen, Yuxing Fei +3
Large language model (LLM) agents currently depend on predefined tools or early-stage tool generation, limiting their adaptability and scalability to complex scientific tasks. We i…
Synthelite: Chemist-aligned and feasibility-aware synthesis planning with LLMs
Nguyen Xuan-Vu, Daniel Armstrong, Milena Wehrbach +3
Computer-aided synthesis planning (CASP) has long been envisioned as a complementary tool for synthetic chemists. However, existing frameworks often lack mechanisms to allow intera…