4 citations · 5 across the 4 of their papers we have counts for
8 papers
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…
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 (…
Uncertainty as a Planning Signal: Multi-Turn Decision Making for Goal-Oriented Conversation
Xinyi Ling, Ye Liu, Reza Averly +1
Goal-oriented conversational systems require making sequential decisions under uncertainty about the user's intent, where the algorithm must balance information acquisition and tar…
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…
LIDDIA: Language-based Intelligent Drug Discovery Agent
Reza Averly, Frazier N. Baker, Ian A. Watson +1
Drug discovery is a long, expensive, and complex process, relying heavily on human medicinal chemists, who can spend years searching the vast space of potential therapies. Recent a…
Entity Decomposition with Filtering: A Zero-Shot Clinical Named Entity Recognition Framework
Reza Averly, Xia Ning
Clinical named entity recognition (NER) aims to retrieve important entities within clinical narratives. Recent works have demonstrated that large language models (LLMs) can achieve…