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Despite its crucial role in research experiments, code correctness is often presumed only on the basis of the perceived quality of results.
Nemo: a toolkit for building ai applications using neural modules
Oleksii Kuchaiev, Jason Li, Huyen Nguyen, Oleksii Hrinchuk, Ryan Leary, Boris Ginsburg, Samuel Kriman, Stanislav Beliaev, Vitaly Lavrukhin, Jack Cook, et al. 2019 · 1909
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Dropout: A simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2014 · 1958
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Toward a theory of test data selection
John B. Goodenough and Susan L. Gerhart. 1975 · 1975
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Data types and program correctness
Barbara H. Liskov. 1975 · 1975
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Design and code inspections to reduce errors in program development
M. E. Fagan. 1976 · 1976
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Factors in software quality
Jim A. McCall, Paul A. Richards, and Gene F. Walters. 1977 · 1977
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Software quality assurance
Fletcher J. Buckley and Robert Poston. 1984 · 1984
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Software Quality Engineering: A Total Technical and Management Approach
Michael S. Deutsch and Ronald R. Willis. 1988 · 1988
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Building Quality Software
Robert L. Glass. 1992 · 1992
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Foundations for the study of software architecture
Dewayne E. Perry and Alexander L. Wolf. 1992 · 1992
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AN INTRODUCTION TO SOFTWARE ARCHITECTURE , pages 1–39
David Garlan and Mary Shaw. 1993 · 1993
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ISO/IEC 9126. Software engineering – Product quality
ISO/IEC. 2001 · 2001
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Test Driven Development. By Example (Addison-Wesley Signature)
Kent Beck. 2002 · 2002
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An initial investigation of test driven development in industry
Boby George and Laurie Williams. 2003 · 2003
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Test-driven development as a defect-reduction practice
Laurie Williams, E. Michael Maximilien, and Mladen Vouk. 2003 · 2003
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Unit testing in practice
Michael Ellims, James Bridges, and Darrel C. Ince. 2004 · 2004
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Statistical significance tests for machine translation evaluation
Philipp Koehn. 2004 · 2004
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The economics of unit testing
Michael Ellims, James Bridges, and Darrel C. Ince. 2006 · 2006
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Connectionist Temporal Classification: Labelling Unsegmented Sequence Data with Recurrent Neural Networks
Alex Graves, Santiago Fernández, Faustino J. Gomez, and Jürgen Schmidhuber. 2006 · 2006
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Continuous Integration: Improving Software Quality and Reducing Risk
Paul M. Duvall, Steve Matyas, and Andrew Glovert. 2007 · 2007
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Automated Defect Prevention: Best Practices in Software Management
Dorota Huizinga and Adam Kolawa. 2007 · 2007
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Do economics journal archives promote replicable research?
Bruce D. McCullough, Kerry A. McGeary, and Teresa D. Harrison. 2008 · 2008
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ISO/IEC 25010 System and software quality models
ISO/IEC. 2010 · 2010
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Reproducible research in computational science
Roger D. Peng. 2011 · 2011
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Believe it or not: how much can we rely on published data on potential drug targets?
Florian Prinz, Thomas Schlange, and Khusru Asadullah. 2011 · 2011
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Software testing and quality assurance: theory and practice
Priyadarshi Tripathy and Kshirasagar Naik. 2011 · 2011
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Expectations, outcomes, and challenges of modern code review
Alberto Bacchelli and Christian Bird. 2013 · 2013
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End-to-end continuous speech recognition using attention-based recurrent nn: First results
Jan Chorowski, Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014 · 2014
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Towards end-to-end speech recognition with recurrent neural networks
Alex Graves and Navdeep Jaitly. 2014 · 2014
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Reproducibility, correctness, and buildability: The three principles for ethical public dissemination of computer science and engineering research
Kristin Y. Rozier and Eric W. D. Rozier. 2014 · 2014
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy. 2015 · 2015
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
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1,500 scientists lift the lid on reproducibility
Monya Baker. 2016 · 2016
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A faceted classification scheme for change-based industrial code review processes
Tobias Baum, Olga Liskin, Kai Niklas, and Kurt Schneider. 2016 · 2016
Cited alongside, same era.
Listen and Translate: A Proof of Concept for End-to-End Speech-to-Text Translation
Alexandre Bérard, Olivier Pietquin, Christophe Servan, and Laurent Besacier. 2016 · 2016
Cited alongside, same era.
The Choice of Code Review Process: A Survey on the State of the Practice
Tobias Baum, Hendrik Leßmann, and Kurt Schneider. 2017 · 2017
Cited alongside, same era.
Language modeling with gated convolutional networks
Yann N. Dauphin, Angela Fan, Michael Auli, and David Grangier. 2017 · 2017
Cited alongside, same era.
Stronger baselines for trustable results in neural machine translation
Michael Denkowski and Graham Neubig. 2017 · 2017
Cited alongside, same era.
Software testing: The state of the practice
Beyond accuracy: Behavioral testing of NLP models with CheckList
Marco Tulio Ribeiro, Tongshuang Wu, Carlos Guestrin, and Sameer Singh. 2020 · 2020
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Green ai
Roy Schwartz, Jesse Dodge, Noah A. Smith, and Oren Etzioni. 2020 · 2020
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fairseq s2t: Fast speech-to-text modeling with fairseq
Changhan Wang, Yun Tang, Xutai Ma, Anne Wu, Dmytro Okhonko, and Juan Pino. 2020 · 2020
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Must-c: A multilingual corpus for end-to-end speech translation
Roldano Cattoni, Mattia Antonino Di Gangi, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021 · 2021
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CTC-based compression for direct speech translation
Marco Gaido, Mauro Cettolo, Matteo Negri, and Marco Turchi. 2021 · 2021
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Recent developments on espnet toolkit boosted by conformer
Pengcheng Guo, Florian Boyer, Xuankai Chang, Tomoki Hayashi, Yosuke Higuchi, Hirofumi Inaguma, Naoyuki Kamo, Chenda Li, Daniel Garcia-Romero, Jiatong Shi, Jing Shi, Shinji Watanabe, Kun Wei, Wangyou Zhang, and Yuekai Zhang. 2021 · 2021
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Mohamad Kassab, Joanna F. DeFranco, and Phillip A. Laplante. 2017 · 2017
Cited alongside, same era.
Searching for activation functions
Prajit Ramachandran, Barret Zoph, and Quoc V. Le. 2017 · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
Sequence-to-Sequence Models Can Directly Translate Foreign Speech
Ron J. Weiss, Jan Chorowski, Navdeep Jaitly, Yonghui Wu, and Zhifeng Chen. 2017 · 2017
Cited alongside, same era.
Speech-transformer: A no-recurrence sequence-to-sequence model for speech recognition
Linhao Dong, Shuang Xu, and Bo Xu. 2018 · 2018
Cited alongside, same era.
The hitchhiker’s guide to testing statistical significance in natural language processing
Rotem Dror, Gili Baumer, Segev Shlomov, and Roi Reichart. 2018 · 2018
Cited alongside, same era.
State of the art: Reproducibility in artificial intelligence
Odd E. Gundersen and Sigbjørn Kjensmo. 2018 · 2018
Cited alongside, same era.
Later among the works it cites.
Non-autoregressive end-to-end speech translation with parallel autoregressive rescoring
Hirofumi Inaguma, Yosuke Higuchi, Kevin Duh, Tatsuya Kawahara, and Shinji Watanabe. 2021 · 2021
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End-to-end audio-visual speech recognition with conformers
Pingchuan Ma, Stavros Petridis, and Maja Pantic. 2021 · 2021
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Scientific credibility of machine translation research: A meta-evaluation of 769 papers
Benjamin Marie, Atsushi Fujita, and Raphael Rubino. 2021 · 2021
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Do transformer modifications transfer across implementations and applications?
Sharan Narang, Hyung Won Chung, Yi Tay, Liam Fedus, Thibault Fevry, Michael Matena, Karishma Malkan, Noah Fiedel, Noam Shazeer, Zhenzhong Lan, Yanqi Zhou, Wei Li, Nan Ding, Jake Marcus, Adam Roberts, and Colin Raffel. 2021 · 2021
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Speechformer: Reducing information loss in direct speech translation
Sara Papi, Marco Gaido, Matteo Negri, and Marco Turchi. 2021 · 2021
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SpeechBrain: A general-purpose speech toolkit
Mirco Ravanelli, Titouan Parcollet, Peter Plantinga, Aku Rouhe, Samuele Cornell, Loren Lugosch, Cem Subakan, Nauman Dawalatabad, Abdelwahab Heba, Jianyuan Zhong, Ju-Chieh Chou, Sung-Lin Yeh, Szu-Wei Fu, Chien-Feng Liao, Elena Rastorgueva, François Grondin, William Aris, Hwidong Na, Yan Gao, Renato De Mori, and Yoshua Bengio. 2021 · 2021
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‘Just What do You Think You’re Doing, Dave?’ A Checklist for Responsible Data Use in NLP
Anna Rogers, Timothy Baldwin, and Kobi Leins. 2021 · 2021
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Stacked acoustic-and-textual encoding: Integrating the pre-trained models into speech translation encoders
Chen Xu, Bojie Hu, Yanyang Li, Yuhao Zhang, Shen Huang, Qi Ju, Tong Xiao, and Jingbo Zhu. 2021 · 2021
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Torchaudio: Building blocks for audio and speech processing
Yao-Yuan Yang, Moto Hira, Zhaoheng Ni, Anjali Chourdia, Artyom Astafurov, Caroline Chen, Ching-Feng Yeh, Christian Puhrsch, David Pollack, Dmitriy Genzel, Donny Greenberg, Edward Z. Yang, Jason Lian, Jay Mahadeokar, Jeff Hwang, Ji Chen, Peter Goldsborough, Prabhat Roy, Sean Narenthiran, Shinji Watanabe, Soumith Chintala, Vincent Quenneville-Bélair, and Yangyang Shi. 2021 · 2021
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Mutual-learning improves end-to-end speech translation
Jiawei Zhao, Wei Luo, Boxing Chen, and Andrew Gilman. 2021 · 2021
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Reproducibility in computational linguistics: Is source code enough?
Mohammad Arvan, Luís Pina, and Natalie Parde. 2022 · 2022
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Toward reusable science with readable code and reproducibility
Layan Bahaidarah, Ethan Hung, Andreas F. De Melo Oliveira, Jyotsna Penumaka, Lukas Rosario, and Ana Trisovic. 2022 · 2022
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A Metrological Perspective on Reproducibility in NLP
Anya Belz. 2022 · 2022
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Quantified reproducibility assessment of NLP results
Anya Belz, Maja Popovic, and Simon Mille. 2022 · 2022
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Efficient yet competitive speech translation: FBK@IWSLT2022
Marco Gaido, Sara Papi, Dennis Fucci, Giuseppe Fiameni, Matteo Negri, and Marco Turchi. 2022 · 2022
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Repairing the cracked foundation: A survey of obstacles in evaluation practices for generated text
Sebastian Gehrmann, Elizabeth Clark, and Thibault Sellam. 2022 · 2022
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Non-autoregressive end-to-end approaches for joint automatic speech recognition and spoken language understanding
Mohan Li and Rama Doddipatla. 2023 · 2022
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Conformer-based self-supervised learning for non-speech audio tasks
Sangeeta Srivastava, Yun Wang, Andros Tjandra, Anurag Kumar, Chunxi Liu, Kritika Singh, and Yatharth Saraf. 2022 · 2022
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The Turing Way: A Handbook for Reproducible Data Science
The Turing Way Community. 2022 · 2022
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A large-scale study on research code quality and execution
Ana Trisovic, Matthew K. Lau, Thomas Pasquier, and Mercè Crosas. 2022 · 2022
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Experimental standards for deep learning research: A natural language processing perspective
Dennis Ulmer, Elisa Bassignana, Max Müller-Eberstein, Daniel Varab, Mike Zhang, Christian Hardmeier, and Barbara Plank. 2022 · 2022
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Revisiting end-to-end speech-to-text translation from scratch
Biao Zhang, Barry Haddow, and Rico Sennrich. 2022 · 2022
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Non-Repeatable Experiments and Non-Reproducible Results: The Reproducibility Crisis in Human Evaluation in NLP
Anya Belz, Craig Thomson, Ehud Reiter, and Simon Mille. 2023 · 2023
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Cost of Testing
Miško Hevery. 2009 · 2023
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The Ecological Footprint of Neural Machine Translation Systems
Dimitar Shterionov and Eva Vanmassenhove. 2023 · 2023
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Efficient Speech Translation with Dynamic Latent Perceivers
Ioannis Tsiamas, Gerard I. Gállego, José A. R. Fonollosa, and Marta R. Costa-jussà. 2023 · 2023
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