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We present $\textbf{MolT5}$ $-$ a self-supervised learning framework for pretraining models on a vast amount of unlabeled natural language text and molecule strings.
Huggingface’s transformers: State-of-the-art natural language processing
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Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases
Ahmet Sureyya Rifaioglu, Heval Atas, Maria Jesus Martin, Rengul Cetin-Atalay, Volkan Atalay, and Tunca Doğan. 2018 · 1912
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Molecular sets (moses): a benchmarking platform for molecular generation models
Daniil Polykovskiy, Alexander Zhebrak, Benjamin Sanchez-Lengeling, Sergey Golovanov, Oktai Tatanov, Stanislav Belyaev, Rauf Kurbanov, Aleksey Artamonov, Vladimir Aladinskiy, Mark Veselov, et al. 2020 · 1931
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Smiles, a chemical language and information system. 1. introduction to methodology and encoding rules
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Smiles. 2. algorithm for generation of unique smiles notation
David Weininger, Arthur Weininger, and Joseph L Weininger. 1989 · 1989
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Automatic image captioning
Jia-Yu Pan, Hyung-Jeong Yang, Pinar Duygulu, and Christos Faloutsos. 2004 · 1990
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Scaling laws for neural language models
Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei. 2020 · 2001
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Reoptimization of mdl keys for use in drug discovery
Joseph L Durant, Burton A Leland, Douglas R Henry, and James G Nourse. 2002 · 2002
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Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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Meteor: An automatic metric for mt evaluation with improved correlation with human judgments
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Levenshtein distance: Information theory, computer science, string (computer science), string metric, damerau? levenshtein distance, spell checker, hamming distance
Frederic P Miller, Agnes F Vandome, and John McBrewster. 2009 · 2009
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Chemberta: Large-scale self-supervised pretraining for molecular property prediction
Seyone Chithrananda, Gabe Grand, and Bharath Ramsundar. 2020 · 2010
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Extended-connectivity fingerprints
David Rogers and Mathew Hahn. 2010 · 2010
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Molecular representation learning with language models and domain-relevant auxiliary tasks
Benedek Fabian, Thomas Edlich, Héléna Gaspar, Marwin Segler, Joshua Meyers, Marco Fiscato, and Mohamed Ahmed. 2020 · 2011
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Efficient estimation of word representations in vector space
Tomás Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013a · 2013
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Learning phrase representations using RNN encoder–decoder for statistical machine translation
Kyunghyun Cho, Bart van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 · 2014
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Molecular fingerprint similarity search in virtual screening
Adrià Cereto-Massagué, María José Ojeda, Cristina Valls, Miquel Mulero, Santiago Garcia-Vallvé, and Gerard Pujadas. 2015 · 2015
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Microsoft coco captions: Data collection and evaluation server
Xinlei Chen, Hao Fang, Tsung-Yi Lin, Ramakrishna Vedantam, Saurabh Gupta, Piotr Dollár, and C. Lawrence Zitnick. 2015 · 2015
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Convolutional networks on graphs for learning molecular fingerprints
David K Duvenaud, Dougal Maclaurin, Jorge Iparraguirre, Rafael Bombarell, Timothy Hirzel, Alán Aspuru-Guzik, and Ryan P Adams. 2015 · 2015
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Get your atoms in order - an open-source implementation of a novel and robust molecular canonicalization algorithm
Nadine Schneider, Roger A. Sayle, and Gregory A. Landrum. 2015 · 2015
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Show and tell: A neural image caption generator
Oriol Vinyals, Alexander Toshev, Samy Bengio, and D. Erhan. 2015 · 2015
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Preparing a collection of radiology examinations for distribution and retrieval
Dina Demner-Fushman, Marc D Kohli, Marc B Rosenman, Sonya E Shooshan, Laritza Rodriguez, Sameer Antani, George R Thoma, and Clement J McDonald. 2016 · 2016
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Generative adversarial text to image synthesis
Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, and Honglak Lee. 2016 · 2016
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Improved deep metric learning with multi-class n-pair loss objective
Kihyuk Sohn. 2016 · 2016
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Multilingual denoising pre-training for neural machine translation
Yinhan Liu, Jiatao Gu, Naman Goyal, Xian Li, Sergey Edunov, Marjan Ghazvininejad, Mike Lewis, and Luke Zettlemoyer. 2020 · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
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VL-BERT: pre-training of generic visual-linguistic representations
Weijie Su, Xizhou Zhu, Yue Cao, Bin Li, Lewei Lu, Furu Wei, and Jifeng Dai. 2020 · 2020
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Automated extraction of chemical synthesis actions from experimental procedures
Alain C Vaucher, Federico Zipoli, Joppe Geluykens, Vishnu H Nair, Philippe Schwaller, and Teodoro Laino. 2020 · 2020
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Molgpt: Molecular generation using a transformer-decoder model
Viraj Bagal, Rishal Aggarwal, PK Vinod, and U Deva Priyakumar. 2021 · 2021
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Ashwin K Vijayakumar, Michael Cogswell, Ramprasath R Selvaraju, Qing Sun, Stefan Lee, David Crandall, and Dhruv Batra. 2016 · 2016
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial networks
Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, and Dimitris N Metaxas. 2017 · 2017
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Mol2vec: unsupervised machine learning approach with chemical intuition
Sabrina Jaeger, Simone Fulle, and Samo Turk. 2018 · 2018
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Entity-aware image caption generation
Di Lu, Spencer Whitehead, Lifu Huang, Heng Ji, and Shih-Fu Chang. 2018 · 2018
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Fréchet chemnet distance: A metric for generative models for molecules in drug discovery
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Text2mol: Cross-modal molecule retrieval with natural language queries
Carl Edwards, ChengXiang Zhai, and Heng Ji. 2021 · 2021
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Utilizing graph machine learning within drug discovery and development
Thomas Gaudelet, Ben Day, Arian R Jamasb, Jyothish Soman, Cristian Regep, Gertrude Liu, Jeremy BR Hayter, Richard Vickers, Charles Roberts, Jian Tang, et al. 2021 · 2021
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Chemformer: A pre-trained transformer for computational chemistry
Ross Irwin, Spyridon Dimitriadis, Jiazhen He, and Esben Bjerrum. 2021 · 2021
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Transformers in vision: A survey
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Rdkit: Open-source cheminformatics software
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Learning transferable visual models from natural language supervision
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Zero-shot text-to-image generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever. 2021 · 2021
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From show to tell: A survey on image captioning
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Bioassayclr: Prediction of biological activity for novel bioassays based on rich textual descriptions
Andreu Vall, Sepp Hochreiter, and Günter Klambauer. 2021 · 2021
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Inferring experimental procedures from text-based representations of chemical reactions
Alain C Vaucher, Philippe Schwaller, Joppe Geluykens, Vishnu H Nair, Anna Iuliano, and Teodoro Laino. 2021 · 2021
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Scaling up vision-language pre-training for image captioning
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Hierarchical text-conditional image generation with clip latents
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Scaling up models and data with t5x
Adam Roberts, Hyung Won Chung, Anselm Levskaya, Gaurav Mishra, James Bradbury, Daniel Andor, Sharan Narang, Brian Lester, Colin Gaffney, Afroz Mohiuddin, Curtis Hawthorne, Aitor Lewkowycz, Alex Salcianu, Marc van Zee, Jacob Austin, Sebastian Goodman, Livio Baldini Soares, Haitang Hu, Sasha Tsvyashchenko, Aakanksha Chowdhery, Jasmijn Bastings, Jannis Bulian, Xavier Garcia, Jianmo Ni, Andrew Chen, Kathleen Kenealy, Jonathan H. Clark, Stephan Lee, Dan Garrette, James Lee-Thorp, Colin Raffel, Noam Shazeer, Marvin Ritter, Maarten Bosma, Alexandre Passos, Jeremy Maitin-Shepard, Noah Fiedel, Mark Omernick, Brennan Saeta, Ryan Sepassi, Alexander Spiridonov, Joshua Newlan, and Andrea Gesmundo. 2022 · 2022
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Chemical-reaction-aware molecule representation learning
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A deep-learning system bridging molecule structure and biomedical text with comprehension comparable to human professionals
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