Fetching the paper…
Reading the bibliography…
Language models pre-trained on scientific literature corpora have substantially advanced scientific discovery by offering high-quality feature representations for downstream applications.
Language models are few-shot learners
Tom B Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 1901
Earlier work this paper cites.
Cloze method: what difference does it make?
Carol A Chapelle and Roberta G Abraham. 1990 · 1990
Earlier work this paper cites.
SMOTE: Synthetic minority over-sampling technique
N V Chawla, K W Bowyer, L O Hall, and W P Kegelmeyer. 2002 · 2002
Earlier work this paper cites.
The NCI60 human tumour cell line anticancer drug screen
Robert H Shoemaker. 2006 · 2006
Earlier work this paper cites.
Visualizing Data using t-SNE
L V D Maaten and Geoffrey E Hinton. 2008 · 2008
Earlier work this paper cites.
Pubtator: a web-based text mining tool for assisting biocuration
Chih-Hsuan Wei, Hung-Yu Kao, and Zhiyong Lu. 2013 · 2013
Earlier work this paper cites.
A Landscape of Pharmacogenomic Interactions in Cancer
Francesco Iorio, Theo A Knijnenburg, Daniel J Vis, Graham R Bignell, Michael P Menden, Michael Schubert, Nanne Aben, Emanuel Gonçalves, Syd Barthorpe, Howard Lightfoot, Thomas Cokelaer, Patricia Greninger, Ewald van Dyk, Han Chang, Heshani de Silva, Holger Heyn, Xianming Deng, Regina K Egan, Qingsong Liu, Tatiana Mironenko, Xeni Mitropoulos, Laura Richardson, Jinhua Wang, Tinghu Zhang, Sebastian Moran, Sergi Sayols, Maryam Soleimani, David Tamborero, Nuria Lopez-Bigas, Petra Ross-Macdonald, Manel Esteller, Nathanael S Gray, Daniel A Haber, Michael R Stratton, Cyril H Benes, Lodewyk F A Wessels, Julio Saez-Rodriguez, Ultan McDermott, and Mathew J Garnett. 2016 · 2016
Earlier work this paper cites.
A unified approach to interpreting model predictions
Scott Lundberg and Su-In Lee. 2017 · 2017
Earlier work this paper cites.
Computational correction of copy number effect improves specificity of CRISPR–Cas9 essentiality screens in cancer cells
Robin M Meyers, Jordan G Bryan, James M McFarland, Barbara A Weir, Ann E Sizemore, Han Xu, Neekesh V Dharia, Phillip G Montgomery, Glenn S Cowley, Sasha Pantel, Amy Goodale, Yenarae Lee, Levi D Ali, Guozhi Jiang, Rakela Lubonja, William F Harrington, Matthew Strickland, Ting Wu, Derek C Hawes, Victor A Zhivich, Meghan R Wyatt, Zohra Kalani, Jaime J Chang, Michael Okamoto, Kimberly Stegmaier, Todd R Golub, Jesse S Boehm, Francisca Vazquez, David E Root, William C Hahn, and Aviad Tsherniak. 2017 · 2017
Earlier work this paper cites.
Learning important features through propagating activation differences
Avanti Shrikumar, Peyton Greenside, and Anshul Kundaje. 2017 · 2017
Earlier work this paper cites.
A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles
Aravind Subramanian, Rajiv Narayan, Steven M Corsello, David D Peck, Ted E Natoli, Xiaodong Lu, Joshua Gould, John F Davis, Andrew A Tubelli, Jacob K Asiedu, David L Lahr, Jodi E Hirschman, Zihan Liu, Melanie Donahue, Bina Julian, Mariya Khan, David Wadden, Ian C Smith, Daniel Lam, Arthur Liberzon, Courtney Toder, Mukta Bagul, Marek Orzechowski, Oana M Enache, Federica Piccioni, Sarah A Johnson, Nicholas J Lyons, Alice H Berger, Alykhan F Shamji, Angela N Brooks, Anita Vrcic, Corey Flynn, Jacqueline Rosains, David Y Takeda, Roger Hu, Desiree Davison, Justin Lamb, Kristin Ardlie, Larson Hogstrom, Peyton Greenside, Nathanael S Gray, Paul A Clemons, Serena Silver, Xiaoyun Wu, Wen-Ning Zhao, Willis Read-Button, Xiaohua Wu, Stephen J Haggarty, Lucienne V Ronco, Jesse S Boehm, Stuart L Schreiber, John G Doench, Joshua A Bittker, David E Root, Bang Wong, and Todd R Golub. 2017 · 2017
Earlier work this paper cites.
Defining a Cancer Dependency Map
Aviad Tsherniak, Francisca Vazquez, Phil G Montgomery, Barbara A Weir, Gregory Kryukov, Glenn S Cowley, Stanley Gill, William F Harrington, Sasha Pantel, John M Krill-Burger, Robin M Meyers, Levi Ali, Amy Goodale, Yenarae Lee, Guozhi Jiang, Jessica Hsiao, William F J Gerath, Sara Howell, Erin Merkel, Mahmoud Ghandi, Levi A Garraway, David E Root, Todd R Golub, Jesse S Boehm, and William C Hahn. 2017 · 2017
Earlier work this paper cites.
DeepSynergy: predicting anti-cancer drug synergy with deep learning
Kristina Preuer, Richard P I Lewis, Sepp Hochreiter, Andreas Bender, Krishna C Bulusu, and Günter Klambauer. 2018 · 2018
Earlier work this paper cites.
Matching the blanks: Distributional similarity for relation learning
Livio Baldini Soares, Nicholas FitzGerald, Jeffrey Ling, and Tom Kwiatkowski. 2019 · 2019
Earlier work this paper cites.
Closed-loop cycles of experiment design, execution, and learning accelerate systems biology model development in yeast
Anthony Coutant, Katherine Roper, Daniel Trejo-Banos, Dominique Bouthinon, Martin Carpenter, Jacek Grzebyta, Guillaume Santini, Henry Soldano, Mohamed Elati, Jan Ramon, Celine Rouveirol, Larisa N Soldatova, and Ross D King. 2019 · 2019
Earlier work this paper cites.
Text-mining in cancer research may help identify effective treatments
Yi-Wen Hsiao and Tzu-Pin Lu. 2019 · 2019
Earlier work this paper cites.
Learning data manipulation for augmentation and weighting
Zhiting Hu, Bowen Tan, Ruslan Salakhutdinov, Tom Mitchell, and Eric P Xing. 2019 · 2019
Earlier work this paper cites.
Submodular optimization-based diverse paraphrasing and its effectiveness in data augmentation
Ashutosh Kumar, Satwik Bhattamishra, Manik Bhandari, and Partha Talukdar. 2019 · 2019
Earlier work this paper cites.
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan Ho So, and Jaewoo Kang. 2019 · 2019
Earlier work this paper cites.
CancerMine: a literature-mined resource for drivers, oncogenes and tumor suppressors in cancer
Jake Lever, Eric Y Zhao, Jasleen Grewal, Martin R Jones, and Steven J M Jones. 2019 · 2019
Earlier work this paper cites.
Unsupervised question answering by cloze translation
Patrick Lewis, Ludovic Denoyer, and Sebastian Riedel. 2019 · 2019
Earlier work this paper cites.
Language models as knowledge bases?
Fabio Petroni, Tim Rocktäschel, Sebastian Riedel, Patrick Lewis, Anton Bakhtin, Yuxiang Wu, and Alexander Miller. 2019 · 2019
Cited alongside, same era.
Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, D Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Cited alongside, same era.
PubTator central: automated concept annotation for biomedical full text articles
Chih-Hsuan Wei, Alexis Allot, Robert Leaman, and Zhiyong Lu. 2019 · 2019
Cited alongside, same era.
Inducing relational knowledge from BERT
Zied Bouraoui, Jose Camacho-Collados, and Steven Schockaert. 2020 · 2020
Cited alongside, same era.
Data manipulation: Towards effective instance learning for neural dialogue generation via learning to augment and reweight
Hengyi Cai, Hongshen Chen, Yonghao Song, Cheng Zhang, Xiaofang Zhao, and Dawei Yin. 2020 · 2020
Cited alongside, same era.
How can we know what language models know?
Exploiting Cloze-Questions for Few-Shot text classification and natural language inference
Timo Schick and Hinrich Schütze. 2021 · 2021
Later among the works it cites.
COVID19 drug repository: text-mining the literature in search of putative COVID19 therapeutics
Dmitry Tworowski, Alessandro Gorohovski, Sumit Mukherjee, Gon Carmi, Eliad Levy, Rajesh Detroja, Sunanda Biswas Mukherjee, and Milana Frenkel-Morgenstern. 2021 · 2021
Later among the works it cites.
Clinical outcome prediction from admission notes using Self-Supervised knowledge integration
Betty van Aken, Jens-Michalis Papaioannou, Manuel Mayrdorfer, Klemens Budde, Felix Gers, and Alexander Loeser. 2021 · 2021
Later among the works it cites.
STraTA: Self-Training with task augmentation for better few-shot learning
Tu Vu, Minh-Thang Luong, Quoc Le, Grady Simon, and Mohit Iyyer. 2021 · 2021
Later among the works it cites.
Few-Shot text classification with triplet networks, data augmentation, and curriculum learning
Jason Wei, Chengyu Huang, Soroush Vosoughi, Yu Cheng, and Shiqi Xu. 2021 · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Zhengbao Jiang, Frank F Xu, Jun Araki, and Graham Neubig. 2020 · 2020
Cited alongside, same era.
Enhanced offensive language detection through data augmentation
Ruibo Liu, Guangxuan Xu, and Soroush Vosoughi. 2020 · 2020
Cited alongside, same era.
CORD-19: The covid-19 open research dataset
Lucy Lu Wang, Kyle Lo, Yoganand Chandrasekhar, Russell Reas, Jiangjiang Yang, Darrin Eide, Kathryn Funk, Rodney Kinney, Ziyang Liu, William Merrill, Paul Mooney, Dewey Murdick, Devvret Rishi, Jerry Sheehan, Zhihong Shen, Brandon Stilson, Alex D Wade, Kuansan Wang, Chris Wilhelm, Boya Xie, Douglas Raymond, Daniel S Weld, Oren Etzioni, and Sebastian Kohlmeier. 2020 · 2020
Cited alongside, same era.
SSMBA: Self-Supervised manifold based data augmentation for improving Out-of-Domain robustness
Nathan Ng, Kyunghyun Cho, and Marzyeh Ghassemi. 2020 · 2020
Cited alongside, same era.
Training question answering models from synthetic data
Raul Puri, Ryan Spring, Mohammad Shoeybi, Mostofa Patwary, and Bryan Catanzaro. 2020 · 2020
Cited alongside, same era.
AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts
Taylor Shin, Yasaman Razeghi, Robert L Logan, IV, Eric Wallace, and Sameer Singh. 2020 · 2020
Cited alongside, same era.
Unsupervised commonsense question answering with Self-Talk
Vered Shwartz, Peter West, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. 2020 · 2020
Cited alongside, same era.
GPT3Mix: Leveraging large-scale language models for text augmentation
Kang Min Yoo, Dongju Park, Jaewook Kang, Sang-Woo Lee, and Woomyoung Park. 2021 · 2021
Later among the works it cites.
Adapting language models for zero-shot learning by meta-tuning on dataset and prompt collections
Ruiqi Zhong, Kristy Lee, Zheng Zhang, and Dan Klein. 2021 · 2021
Later among the works it cites.
Text-Mining approach to identify hub genes of cancer metastasis and potential drug repurposing to target them
Trishna Saha Detroja, Hava Gil-Henn, and Abraham O Samson. 2022 · 2022
Later among the works it cites.
Effective drug combinations in breast, colon and pancreatic cancer cells
Patricia Jaaks, Elizabeth A Coker, Daniel J Vis, Olivia Edwards, Emma F Carpenter, Simonetta M Leto, Lisa Dwane, Francesco Sassi, Howard Lightfoot, Syd Barthorpe, Dieudonne van der Meer, Wanjuan Yang, Alexandra Beck, Tatiana Mironenko, Caitlin Hall, James Hall, Iman Mali, Laura Richardson, Charlotte Tolley, James Morris, Frances Thomas, Ermira Lleshi, Nanne Aben, Cyril H Benes, Andrea Bertotti, Livio Trusolino, Lodewyk Wessels, and Mathew J Garnett. 2022 · 2022
Later among the works it cites.
Modular and Parameter-Efficient multimodal fusion with prompting
Sheng Liang, Mengjie Zhao, and Hinrich Schuetze. 2022 · 2022
Later among the works it cites.
Pisces: A cross-modal contrastive learning approach to synergistic drug combination prediction
Jiacheng Lin, Hanwen Xu, Addie Woicik, Jianzhu Ma, and Sheng Wang. 2022 · 2022
Later among the works it cites.
BioGPT: generative pre-trained transformer for biomedical text generation and mining
Renqian Luo, Liai Sun, Yingce Xia, Tao Qin, Sheng Zhang, Hoifung Poon, and Tie-Yan Liu. 2022 · 2022
Later among the works it cites.
Leveraging QA datasets to improve generative data augmentation
Dheeraj Mekala, Tu Vu, Timo Schick, and Jingbo Shang. 2022 · 2022
Later among the works it cites.
Generating training data with language models: Towards zero-shot language understanding
Yu Meng, Jiaxin Huang, Yu Zhang, and Jiawei Han. 2022 · 2022
Later among the works it cites.
Literature-Augmented clinical outcome prediction
Aakanksha Naik, Sravanthi Parasa, Sergey Feldman, Lucy Lu Wang, and Tom Hope. 2022 · 2022
Later among the works it cites.
A novel approach to predicting the synergy of anti-cancer drug combinations using document-based feature extraction
Yongsun Shim, Munhwan Lee, Pil-Jong Kim, and Hong-Gee Kim. 2022 · 2022
Later among the works it cites.
PromDA: Prompt-based data augmentation for Low-Resource NLU tasks
Yufei Wang, Can Xu, Qingfeng Sun, Huang Hu, Chongyang Tao, Xiubo Geng, and Daxin Jiang. 2022 · 2022
Later among the works it cites.
Chain of thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H Chi, Quoc V Le, and Denny Zhou. 2022 · 2022
Later among the works it cites.
ZeroGen: Efficient zero-shot learning via dataset generation
Jiacheng Ye, Jiahui Gao, Qintong Li, Hang Xu, Jiangtao Feng, Zhiyong Wu, Tao Yu, and Lingpeng Kong. 2022 · 2022
Later among the works it cites.
Large language models are Human-Level prompt engineers
Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, Keiran Paster, Silviu Pitis, Harris Chan, and Jimmy Ba. 2022 · 2022
Later among the works it cites.