6 citations · 9 across the 8 of their papers we have counts for
13 papers
MFG: Multi-turn Feedback Guided Molecular Optimization
Trieu Nguyen, Frazier N. Baker, Ruoxi Gao +2
Multi-objective molecular optimization is a critical process in drug discovery that aims to modify a given molecule to simultaneously improve multiple properties while maintaining…
ChemExplain: A Multimodal Benchmark for Explanatory Chemical Reasoning
Aotian Chen, Frazier N. Baker, Reza Averly +5
Current chemistry benchmarks primarily evaluate outcome prediction or reaction pathway generation, but rarely test whether a model can explain why an observed chemical effect occur…
MADDIE: Multi-Agent Drug Discovery Engine
Ye Liu, Reza Averly, Avery Meyer +4
Drug discovery remains a resource-intensive and time-consuming process, involving billions of dollars and a decade of development to advance a drug to market. While many in silico…
FREA: A Multi-Source Expert Benchmark for Reaction Feasibility Verification
Botao Yu, Bo Zhou, Daniel Adu-Ampratwum +7
As generative models and AI agents propose chemical reactions at a scale beyond expert review, feasibility verifiers decide which proposals enter synthesis planning. But do their d…
ARMOR: An Agentic Framework for Reaction Feasibility Prediction via Adaptive Utility-aware Multi-tool Reasoning
Ye Liu, Botao Yu, Xinyi Ling +2
Reaction feasibility prediction, as a fundamental problem in computational chemistry, has benefited from diverse tools enabled by recent advances in artificial intelligence, partic…
MMORF: A Multi-agent Framework for Designing Multi-objective Retrosynthesis Planning Systems
Frazier N. Baker, Trieu Nguyen, Reza Averly +4
Multi-objective retrosynthesis planning is a critical chemistry task requiring dynamic balancing of quality, safety, and cost objectives. Language model-based multi-agent systems (…
ScholarEval: Research Idea Evaluation Grounded in Literature
Hanane Nour Moussa, Patrick Queiroz Da Silva, Daniel Adu-Ampratwum +7
As AI tools become increasingly common for research ideation, robust evaluation is critical to ensure the validity and usefulness of generated ideas. We introduce ScholarEval, a re…
LARC: Towards Human-level Constrained Retrosynthesis Planning through an Agentic Framework
Frazier N. Baker, Daniel Adu-Ampratwum, Reza Averly +3
Large language model (LLM) agent evaluators leverage specialized tools to ground the rational decision-making of LLMs, making them well-suited to aid in scientific discoveries, suc…
DiffER: Categorical Diffusion for Chemical Retrosynthesis
Sean Current, Ziqi Chen, Daniel Adu-Ampratwum +2
Methods for automatic chemical retrosynthesis have found recent success through the application of models traditionally built for natural language processing, primarily through tra…
Generating 3D Binding Molecules Using Shape-Conditioned Diffusion Models with Guidance
Ziqi Chen, Bo Peng, Tianhua Zhai +2
Drug development is a critical but notoriously resource- and time-consuming process. In this manuscript, we develop a novel generative artificial intelligence (genAI) method DiffSM…
ChemToolAgent: The Impact of Tools on Language Agents for Chemistry Problem Solving
Botao Yu, Frazier N. Baker, Ziru Chen +5
To enhance large language models (LLMs) for chemistry problem solving, several LLM-based agents augmented with tools have been proposed, such as ChemCrow and Coscientist. However,…
log-RRIM: Yield Prediction via Local-to-global Reaction Representation Learning and Interaction Modeling
Xiao Hu, Ziqi Chen, Bo Peng +2
Accurate prediction of chemical reaction yields is crucial for optimizing organic synthesis, potentially reducing time and resources spent on experimentation. With the rise of arti…
ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery
Ziru Chen, Shijie Chen, Yuting Ning +17
The advancements of large language models (LLMs) have piqued growing interest in developing LLM-based language agents to automate scientific discovery end-to-end, which has sparked…