Fetching the paper…
Reading the bibliography…
"Attention is all you need" has become a fundamental precept in machine learning research.
Principles of neurodynamics. perceptrons and the theory of brain mechanisms
Frank Rosenblatt. 1961 · 1961
Earlier work this paper cites.
Explanation and scientific understanding
Michael Friedman. 1974 · 1974
Earlier work this paper cites.
A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position
Kunihiko Fukushima. 1980 · 1980
Earlier work this paper cites.
Explanatory unification
Philip Kitcher. 1981 · 1981
Earlier work this paper cites.
A learning algorithm for Boltzmann machines
David H Ackley, Geoffrey E Hinton, and Terrence J Sejnowski. 1985 · 1985
Earlier work this paper cites.
Parallel distributed processing . Vol. 2
James L McClelland, David E Rumelhart, PDP Research Group, et al · 1986
Earlier work this paper cites.
The morality of freedom
Joseph Raz. 1986 · 1986
Earlier work this paper cites.
Learning representations by back-propagating errors
David E Rumelhart, Geoffrey E Hinton, and Ronald J Williams. 1986 · 1986
Earlier work this paper cites.
Situated knowledges: The science question in feminism and the privilege of partial perspective
Donna Haraway. 1988 · 1988
Earlier work this paper cites.
One AI or many?
Seymour Papert. 1988 · 1988
Earlier work this paper cites.
The view from nowhere
Thomas Nagel. 1989 · 1989
Earlier work this paper cites.
The structure of ill-structured solutions: Boundary objects and heterogeneous distributed problem solving
Susan Leigh Star. 1989 · 1989
Earlier work this paper cites.
A logical calculus of the ideas immanent in nervous activity
Warren S McCulloch and Walter Pitts. 1990 · 1990
Earlier work this paper cites.
“Strong objectivity”: A response to the new objectivity question
Sandra Harding. 1995 · 1995
Earlier work this paper cites.
Path dependence, lock-in, and history
Stan J Liebowitz and Stephen E Margolis. 1995 · 1995
Earlier work this paper cites.
Idealism and the Sociology of Knowledge
David Bloor. 1996 · 1996
Earlier work this paper cites.
A sociological study of the official history of the perceptrons controversy
Mikel Olazaran. 1996 · 1996
Earlier work this paper cites.
Image and logic: A material culture of microphysics
Peter Galison et al · 1997
Earlier work this paper cites.
No free lunch theorems for optimization
David H Wolpert and William G Macready. 1997 · 1997
Earlier work this paper cites.
Six principles for biologically based computational models of cortical cognition
Randall C O’Reilly. 1998 · 1998
Earlier work this paper cites.
What is the Point of Equality?
Elizabeth S Anderson. 1999 · 1999
Earlier work this paper cites.
The dappled world: A study of the boundaries of science
Nancy Cartwright et al · 1999
Earlier work this paper cites.
Selection and the extent of explanatory unification
Robert A Skipper Jr. 1999 · 1999
Earlier work this paper cites.
Path dependence in historical sociology
James Mahoney. 2000 · 2000
Earlier work this paper cites.
Explanatory unification: Double and doubtful
Uskali Mäki. 2001 · 2001
Earlier work this paper cites.
Finite-time analysis of the multiarmed bandit problem
Peter Auer, Nicolo Cesa-Bianchi, and Paul Fischer. 2002 · 2002
Earlier work this paper cites.
Trust and vulnerability in open source software
Scott A. Hissam, Daniel Plakosh, and C Weinstock. 2002 · 2002
Earlier work this paper cites.
A Bayesian account of the virtue of unification
Wayne C Myrvold. 2003 · 2003
Earlier work this paper cites.
Two uses of unification
Elliott Sober. 2003 · 2003
Earlier work this paper cites.
Groups of diverse problem solvers can outperform groups of high-ability problem solvers
Lu Hong and Scott E Page. 2004 · 2004
Earlier work this paper cites.
Diverse ensembles for active learning. In Proceedings of the twenty-first international conference on Machine learning . 74
Prem Melville and Raymond J Mooney. 2004 · 2004
Earlier work this paper cites.
Explanatory unification and the early synthesis
Anya Plutynski. 2005 · 2005
Earlier work this paper cites.
The epistemic benefit of transient diversity
Kevin JS Zollman. 2010 · 2010
Earlier work this paper cites.
Is chess the drosophila of artificial intelligence? A social history of an algorithm
Nathan Ensmenger. 2012 · 2012
Earlier work this paper cites.
Raw data is an oxymoron
Lisa Gitelman (Ed.). 2013 · 2013
Earlier work this paper cites.
In search of the real inductive bias: On the role of implicit regularization in deep learning
Behnam Neyshabur, Ryota Tomioka, and Nathan Srebro. 2014 · 2014
Earlier work this paper cites.
TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dandelion Mané, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng. 2015 · 2015
Earlier work this paper cites.
Why m heads are better than one: Training a diverse ensemble of deep networks
Stefan Lee, Senthil Purushwalkam, Michael Cogswell, David Crandall, and Dhruv Batra. 2015 · 2015
Earlier work this paper cites.
The epistemic division of labor revisited
Johanna Thoma. 2015 · 2015
Earlier work this paper cites.
Deep Learning
Ian Goodfellow, Yoshua Bengio, and Aaron Courville. 2016 · 2016
Cited alongside, same era.
Future progress in artificial intelligence: A survey of expert opinion
Vincent C Müller and Nick Bostrom. 2016 · 2016
Cited alongside, same era.
Superintelligence: Paths, Dangers, Strategies
Nick Bostrom. 2017 · 2017
Cited alongside, same era.
Building machines that learn and think like people
Brenden M Lake, Tomer D Ullman, Joshua B Tenenbaum, and Samuel J Gershman. 2017 · 2017
Cited alongside, same era.
Perceptrons: An introduction to computational geometry
Marvin Minsky and Seymour A Papert. 2017 · 2017
Cited alongside, same era.
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
Cited alongside, same era.
The Impossibility of Automating Ambiguity
Abeba Birhane. 2021 · 2021
Later among the works it cites.
On the opportunities and risks of foundation models
Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al · 2021
Later among the works it cites.
Attention Approximates Sparse Distributed Memory
Trenton Bricken and Cengiz Pehlevan. 2021 · 2021
Later among the works it cites.
Rigour versus the need for evidential diversity
Nancy Cartwright. 2021 · 2021
Later among the works it cites.
An attentive survey of attention models
Sneha Chaudhari, Varun Mithal, Gungor Polatkan, and Rohan Ramanath. 2021 · 2021
Later among the works it cites.
The Batch
DeepLearning.AI. 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…
The ethics of artificial intelligence
Nick Bostrom and Eliezer Yudkowsky. 2018 · 2018
Cited alongside, same era.
Tom Everitt, Gary Lea, and Marcus Hutter. 2018 · 2018
Cited alongside, same era.
Explaining explanations: An overview of interpretability of machine learning. In 2018 IEEE 5th International Conference on data science and advanced analytics (DSAA) . IEEE, 80–89
Leilani H Gilpin, David Bau, Ben Z Yuan, Ayesha Bajwa, Michael Specter, and Lalana Kagal. 2018 · 2018
Cited alongside, same era.
A short-term intervention for long-term fairness in the labor market. In Proceedings of the 2018 World Wide Web Conference . 1389–1398
Lily Hu and Yiling Chen. 2018 · 2018
Cited alongside, same era.
Algorithms of oppression
Safiya Umoja Noble. 2018 · 2018
Cited alongside, same era.
FactSheets: Increasing trust in AI services through supplier’s declarations of conformity
Matthew Arnold, Rachel KE Bellamy, Michael Hind, Stephanie Houde, Sameep Mehta, Aleksandra Mojsilović, Ravi Nair, K Natesan Ramamurthy, Alexandra Olteanu, David Piorkowski, et al · 2019
Cited alongside, same era.
Datasheets for datasets
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé Iii, and Kate Crawford. 2021 · 2021
Later among the works it cites.
The false hope of current approaches to explainable artificial intelligence in health care
Marzyeh Ghassemi, Luke Oakden-Rayner, and Andrew L Beam. 2021 · 2021
Later among the works it cites.
The hardware lottery
Sara Hooker. 2021 · 2021
Later among the works it cites.
Algorithmic monoculture and social welfare
Jon Kleinberg and Manish Raghavan. 2021 · 2021
Later among the works it cites.
Why AI is harder than we think
Melanie Mitchell. 2021 · 2021
Later among the works it cites.
Multi-modal fusion transformer for end-to-end autonomous driving. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 7077–7087
Aditya Prakash, Kashyap Chitta, and Andreas Geiger. 2021 · 2021
Later among the works it cites.
AI and the everything in the whole wide world benchmark
Inioluwa Deborah Raji, Emily M Bender, Amandalynne Paullada, Emily Denton, and Alex Hanna. 2021 · 2021
Later among the works it cites.
Five reasons to embrace Transformer in computer vision
Microsoft Research. 2021 · 2021
Later among the works it cites.
The Capability Approach
Ingrid Robeyns and Morten Fibieger Byskov. 2021 · 2021
Later among the works it cites.
The steep cost of capture
Meredith Whittaker. 2021 · 2021
Later among the works it cites.
Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State
Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Yisen Wang, and Zhouchen Lin. 2021 · 2021
Later among the works it cites.
Trends in NLP with John Bohannon
John Bohannon and Sam Charrington. 2022 · 2022
Closest in time.
Deep Problems with Neural Network Models of Human Vision
Jeffrey Bowers, Gaurav Malhotra, Marin Dujmović, Milton Llera Montero, Christian Tsvetkov, Valerio Biscione, Guillermo Puebla, Federico Adolfi, John Hummel, Rachel Flood Heaton, Benjamin Evans, Jeff Mitchell, and Ryan Blything. 2022 · 2022
Closest in time.
JAX: composable transformations of Python+NumPy programs
James Bradbury, Roy Frostig, Peter Hawkins, Matthew James Johnson, Chris Leary, Dougal Maclaurin, George Necula, Adam Paszke, Jake VanderPlas, Skye Wanderman-Milne, and Qiao Zhang. 2018 · 2022
Closest in time.
AI Now 2017 Report
Alex Campolo, Madelyn Sanfilippo, Meredith Whittaker, and Kate Crawford. 2017 · 2022
Closest in time.
The Unity of Science
Jordi Cat. 2022 · 2022
Closest in time.
Trends in Computer Vision with Georgia Gkioxari
Sam Charrington and Georgia Gkioxari. 2022 · 2022
Closest in time.
Human Help Wanted: Why AI Is Terrible at Content Moderation
Ben Dickson. 2019 · 2022
Closest in time.
huggingface (Hugging Face)
Hugging Face. n.d. · 2022
Closest in time.
The ongoing consolidation in AI is incredible…
@karpathy (Andrej Karpathy). 2021 · 2022
Closest in time.
Are AI ethics teams doomed to be a facade? Women who pioneered them weigh in
Sage Lazzaro. 2021 · 2022
Closest in time.
Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, and Saining Xie. 2022 · 2022
Closest in time.
Log4j Is One Big “I Told You So” for Open Source Communities
Mike Melanson. 2021 · 2022
Closest in time.
State of AI Report: Transformers Are Taking the AI World by Storm
John. P. Mellow Jr. 2022 · 2022
Closest in time.
Will Transformers Take Over Artificial Intelligence?
Stephen Ornes. 2022 · 2022
Closest in time.
Image Classification on ImageNet
Papers With Code. 2022a · 2022
Closest in time.
Machine Translation on WMT2014 English-German
Papers With Code. 2022b · 2022
Closest in time.
Object Detection on COCO test-dev
Papers With Code. 2022c · 2022
Closest in time.
Question Answering on SQuAD1.1
Papers With Code. 2022d · 2022
Closest in time.
Semantic Segmentation on ADE20K
Papers With Code. 2022e · 2022
Closest in time.
Sentiment Analysis on SST-2 Binary classification
Papers With Code. 2022f · 2022
Closest in time.
Speech Recognition on LibriSpeech test-clean
Papers With Code. 2022g · 2022
Closest in time.