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Posts by Collection
portfolio
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publications
ReLM: Leveraging Language Models for Enhanced Chemical Reaction Prediction
Published in findings of EMNLP, 2023
In this work, we propose ReLM, a novel framework that leverages the chemical knowledge encoded in language models (LMs) to assist GNNs, thereby enhancing the accuracy of real-world chemical reaction predictions.
Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules
Published in NeurIPS, 2024
In this paper, we summarize previous works on Masked Graph Modeling (MGM) for molecules and propose a novel MGM model, SimSGT, featuring a Simple GNN-based Tokenizer (SGT) and an effective decoding strategy.
ReactXT: Understanding Molecular” Reaction-ship” via Reaction-Contextualized Molecule-Text Pretraining
Published in findings of ACL, 2024
In this paper, we propose a novel pretraining paradigm, named ReactXT, to learn molecule-text representations that are contextualized by chemicalreaction contexts. We also introduce a new benchmark dataset, OpenExp, for evaluating the models on the task of experimental procedure prediction.
talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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