Zhengkai Tu — accepted AI-conference papers

2023

FusionRetro: Molecule Representation Fusion via In-Context Learning for Retrosynthetic Planning

Songtao Liu, Zhengkai Tu, Minkai Xu, Zuobai Zhang, Lu Lin, Zhitao Ying +3

ICML 2023poster

Retrosynthetic planning aims to devise a complete multi-step synthetic route from starting materials to a target molecule. Current strategies use a decoupled approach of single-step retrosynthesis models and search algorithms, taking only the product as the input to predict the reactants for each pl…

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2023

Predictive Chemistry Augmented with Text Retrieval

Yujie Qian, Zhening Li, Zhengkai Tu, Connor W. Coley, Regina Barzilay

EMNLP 2023long main

This paper focuses on using natural language descriptions to enhance predictive models in the chemistry field. Conventionally, chemoinformatics models are trained with extensive structured data manually extracted from the literature. In this paper, we introduce TextReact, a novel method that directl…

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