Who Cited It

On the Opportunities and Risks of Foundation Models

2021 · arXiv (Cornell University) · 2,265 citations · 3 from inside this corpus

Rishi Bommasani, Drew A. Hudson low, Ehsan Adeli, Russ B. Altman, Simran Arora, Sydney von Arx low, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch low, Dallas Card, Rodrigo Castellon low, Niladri S. Chatterji low, Annie Chen, Kathleen Creel, Jared Quincy Davis low, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy low, Kawin Ethayarajh low, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel low, Noah D. Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong low, Kyle Hsu low, Jing Huang, Thomas Icard low, Saahil Jain low, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani low, Omar Khattab low, Pang Wei Koh, Mark Krass low, Ranjay Krishna, Rohith Kuditipudi low, Ananya Kumar, Faisal Ladhak, Mina Lee, Tong Lee, Jure Leskovec, Isabelle Levent low, Xiang Lisa Li, Xuechen Li, Tengyu Ma, Ali Ahmad Malik, Christopher D. Manning, Suvir Mirchandani low, Eric Mitchell, Zanele Munyikwa low, Suraj Nair, Avanika Narayan low, Deepak Narayanan, Benjamin T. Newman, Allen Nie, Juan Carlos Niebles, Hamed Nilforoshan low, Julian Nyarko, Giray Ogut low, Laurel Orr, Isabel Papadimitriou low, Joon-Sung Park, Chris Piech, Eva Portelance, Christopher Potts, Aditi Raghunathan low, Rob Reich low, Hongyu Ren, Frieda Rong low, Yusuf Roohani, Camilo Ruiz, Jack Ryan low, Christopher Ré low, Dorsa Sadigh, Shiori Sagawa low, Keshav Santhanam, Andy Shih low, Krishnan Srinivasan, Alex Tamkin, Rohan Taori, Armin W. Thomas, Florian Tramèr, Rose E. Wang low, William Yang Wang

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

On the Opportunities and Risks of Foundation Models (2021)On the Opportunities and Risk…Long Short-Term Memory (1997)Long Short-Term MemoryGlove: Global Vectors for Word Representation (2014)Glove: Global Vectors for Wor…BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (2019)BERT: Pre-training of Deep Bi…HISTORIAE, History of Socio-Cultural Transformation as Linguistic Data Science. A Humanit… (2019)HISTORIAE, History of Socio-C…A Fast Learning Algorithm for Deep Belief Nets (2006)A Fast Learning Algorithm for…Mastering the game of Go with deep neural networks and tree search (2016)Mastering the game of Go with…Auto-Encoding Variational Bayes (2013)Auto-Encoding Variational Bay…No free lunch theorems for optimization (1997)Distilling the Knowledge in a Neural Network (2015)Distilling the Knowledge in a…On a Method to Measure Supervised Multiclass Model’s Interpretability: Application to Deg… (2024)On a Method to Measure Superv…Understanding the difficulty of training deep feedforward neural networks (2010)Understanding the difficulty …Momentum Contrast for Unsupervised Visual Representation Learning (2020)Momentum Contrast for Unsuper…Efficient Estimation of Word Representations in Vector Space (2013)Efficient Estimation of Word …Causality (2009)CausalityStop explaining black box machine learning models for high stakes decisions and use inter… (2019)Stop explaining black box mac…The Graph Neural Network Model (2008)Deep Learning (2016)Deep LearningTransformers: State-of-the-Art Natural Language Processing (2020)Transformers: State-of-the-Ar…Ensemble Methods in Machine Learning (2000)Ensemble Methods in Machine L…Overcoming catastrophic forgetting in neural networks (2017)Overcoming catastrophic forge…[No title in the source record — Edinburgh Research Explorer (University of Edinburgh)][No title in the source recor…Calibrating Noise to Sensitivity in Private Data Analysis (2006)Calibrating Noise to Sensitiv…SQuAD: 100,000+ Questions for Machine Comprehension of Text (2016)SQuAD: 100,000+ Questions for…On the Dangers of Stochastic Parrots (2021)On the Dangers of Stochastic …Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks (2017)Model-Agnostic Meta-Learning …Recurrent neural network based language model (2010)Recurrent neural network base…A unified architecture for natural language processing (2008)A unified architecture for na…Prototypical Networks for Few-shot Learning (2017)Prototypical Networks for Few…[No title in the source record — Edinburgh Research Explorer (University of Edinburgh)][No title in the source recor…DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter (2019)DistilBERT, a distilled versi…Membership Inference Attacks Against Machine Learning Models (2017)Membership Inference Attacks …Speech and Language Processing: An Introduction to Natural Language Processing, Computati… (2000)Speech and Language Processin…ALBERT: A Lite BERT for Self-supervised Learning of Language\n Representations (2019)Large language models encode clinical knowledge (2023)Large language models encode …A Survey on Evaluation of Large Language Models (2024)A Survey on Evaluation of Lar…A Brief Overview of ChatGPT: The History, Status Quo and Potential Future Development (2023)A Brief Overview of ChatGPT: …
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What this paper cites, inside the corpus

PaperYearCited
Long Short-Term Memory1997101,359
Glove: Global Vectors for Word Representation201434,067
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding201933,416
HISTORIAE, History of Socio-Cultural Transformation as Linguistic Data Science. A Humanit…201917,489
A Fast Learning Algorithm for Deep Belief Nets200616,540
Mastering the game of Go with deep neural networks and tree search201616,014
Auto-Encoding Variational Bayes201315,583
No free lunch theorems for optimization199714,234
Distilling the Knowledge in a Neural Network201514,099
On a Method to Measure Supervised Multiclass Model’s Interpretability: Application to Deg…202413,528
Understanding the difficulty of training deep feedforward neural networks201012,673
Momentum Contrast for Unsupervised Visual Representation Learning202012,515
Efficient Estimation of Word Representations in Vector Space201311,714
Causality200911,477
Stop explaining black box machine learning models for high stakes decisions and use inter…20199,924
The Graph Neural Network Model20089,662
Deep Learning20168,952
Transformers: State-of-the-Art Natural Language Processing20208,295
Ensemble Methods in Machine Learning20008,058
Overcoming catastrophic forgetting in neural networks20177,624
[No title in the source record — Edinburgh Research Explorer (University of Edinburgh)]7,291
Calibrating Noise to Sensitivity in Private Data Analysis20067,210
SQuAD: 100,000+ Questions for Machine Comprehension of Text20166,435
On the Dangers of Stochastic Parrots20216,426
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks20175,794
Recurrent neural network based language model20105,432
A unified architecture for natural language processing20085,207
Prototypical Networks for Few-shot Learning20175,204
[No title in the source record — Edinburgh Research Explorer (University of Edinburgh)]4,858
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter20194,600
Membership Inference Attacks Against Machine Learning Models20174,490
Speech and Language Processing: An Introduction to Natural Language Processing, Computati…20004,170
ALBERT: A Lite BERT for Self-supervised Learning of Language\n Representations20194,076

What cites it, inside the corpus

PaperYearCited
Large language models encode clinical knowledge20233,721
A Survey on Evaluation of Large Language Models20242,736
A Brief Overview of ChatGPT: The History, Status Quo and Potential Future Development20231,444

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Topics

Domain Adaptation and Few-Shot LearningComputer Science
Adversarial Robustness in Machine LearningComputer Science
Topic ModelingComputer Science

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