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AI powered code-recommendation systems, such as Copilot and CodeWhisperer, provide code suggestions inside a programmer's environment (e.g., an IDE) with the aim of improving productivity.
Attention-sensitive alerting
Eric Horvitz, Andy Jacobs, and David Hovel · 1999
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Principles of mixed-initiative user interfaces
Eric Horvitz · 1999
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The effects of interruptions on task performance, annoyance, and anxiety in the user interface
Brian P Bailey, Joseph A Konstan, and John V Carlis · 2001
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Notification, disruption, and memory: Effects of messaging interruptions on memory and performance
Edward Cutrell, Mary Czerwinski, and Eric Horvitz · 2001
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Learning and reasoning about interruption
Eric Horvitz and Johnson Apacible · 2003
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Tamer: Training an agent manually via evaluative reinforcement
W Bradley Knox and Peter Stone · 2008
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A survey of collaborative filtering techniques
Xiaoyuan Su and Taghi M Khoshgoftaar · 2009
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Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay · 2011
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Flow and the foundations of positive psychology
Mihaly Csikszentmihalyi and Reed Larson · 2014
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Xgboost: extreme gradient boosting
Tianqi Chen, Tong He, Michael Benesty, Vadim Khotilovich, Yuan Tang, Hyunsu Cho, Kailong Chen, et al · 2015
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Obtaining well calibrated probabilities using bayesian binning
Mahdi Pakdaman Naeini, Gregory Cooper, and Milos Hauskrecht · 2015
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XGBoost: A scalable tree boosting system
Tianqi Chen and Carlos Guestrin · 2016
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Deep reinforcement learning from human preferences
Paul F Christiano, Jan Leike, Tom Brown, Miljan Martic, Shane Legg, and Dario Amodei · 2017
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Interactive learning from policy-dependent human feedback
James MacGlashan, Mark K Ho, Robert Loftin, Bei Peng, Guan Wang, David L Roberts, Matthew E Taylor, and Michael L Littman · 2017
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A review of user interface design for interactive machine learning
John J Dudley and Per Ola Kristensson · 2018
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Predict responsibly: improving fairness and accuracy by learning to defer
David Madras, Toni Pitassi, and Richard Zemel · 2018
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Beyond accuracy: The role of mental models in human-ai team performance
Gagan Bansal, Besmira Nushi, Ece Kamar, Walter S Lasecki, Daniel S Weld, and Eric Horvitz · 2019
Cited alongside, same era.
Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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Fine-tuning language models from human preferences
Daniel M Ziegler, Nisan Stiennon, Jeffrey Wu, Tom B Brown, Alec Radford, Dario Amodei, Paul Christiano, and Geoffrey Irving · 2019
Cited alongside, same era.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
Github copilot - your ai pair programmer, 2022
Github · 2022
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Research: Quantifying github copilot’s impact on developer productivity and happiness, Sep 2022
Eirini Kalliamvakou · 2022
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Competition-level code generation with alphacode
Yujia Li, David Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, et al · 2022
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Reading between the lines: Modeling user behavior and costs in ai-assisted programming
Hussein Mozannar, Gagan Bansal, Adam Fourney, and Eric Horvitz · 2022
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Teaching humans when to defer to a classifier via exemplars
Hussein Mozannar, Arvind Satyanarayan, and David Sontag · 2022
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Cited alongside, same era.
Codebert: A pre-trained model for programming and natural languages
Zhangyin Feng, Daya Guo, Duyu Tang, Nan Duan, Xiaocheng Feng, Ming Gong, Linjun Shou, Bing Qin, Ting Liu, Daxin Jiang, et al · 2020
Cited alongside, same era.
Consistent estimators for learning to defer to an expert
Hussein Mozannar and David Sontag · 2020
Cited alongside, same era.
Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al · 2021
Cited alongside, same era.
Measuring coding challenge competence with apps
Dan Hendrycks, Steven Basart, Saurav Kadavath, Mantas Mazeika, Akul Arora, Ethan Guo, Collin Burns, Samir Puranik, Horace He, Dawn Song, et al · 2021
Cited alongside, same era.
Differentiable learning under triage
Nastaran Okati, Abir De, and Manuel Rodriguez · 2021
Cited alongside, same era.
Perfection not required? human-ai partnerships in code translation
Justin D Weisz, Michael Muller, Stephanie Houde, John Richards, Steven I Ross, Fernando Martinez, Mayank Agarwal, and Kartik Talamadupula · 2021
Cited alongside, same era.
Ml-powered coding companion – amazon codewhisperer, 2022
Amazon · 2022
Cited alongside, same era.
Chatgpt: Optimizing language models for dialogue, 2022
OpenAI · 2022
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Learning to prevent profitless neural code completion
Zhensu Sun, Xiaoning Du, Fu Song, Shangwen Wang, Mingze Ni, and Li Li · 2022
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What is it like to program with artificial intelligence?
Advait Sarkar, Andrew D Gordon, Carina Negreanu, Christian Poelitz, Sruti Srinivasa Ragavan, and Ben Zorn · 2022
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Ml-enhanced code completion improves developer productivity, Jul 2022
Maxim Tabachnyk Tabachnyk and Stoyan Nikolov · 2022
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Expectation vs. experience: Evaluating the usability of code generation tools powered by large language models
Priyan Vaithilingam, Tianyi Zhang, and Elena L Glassman · 2022
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Productivity assessment of neural code completion
Albert Ziegler, Eirini Kalliamvakou, X Alice Li, Andrew Rice, Devon Rifkin, Shawn Simister, Ganesh Sittampalam, and Edward Aftandilian · 2022
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Learning personalized decision support policies
Umang Bhatt, Valerie Chen, Katherine M Collins, Parameswaran Kamalaruban, Emma Kallina, Adrian Weller, and Ameet Talwalkar · 2023
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Tree-sitter parser generator tool, Jan 2023
Eirini Kalliamvakou · 2023
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When to show a suggestion? integrating human feedback in ai-assisted programming
Hussein Mozannar, Gagan Bansal, Adam Fourney, and Eric Horvitz · 2023
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Direct preference optimization: Your language model is secretly a reward model
Rafael Rafailov, Archit Sharma, Eric Mitchell, Stefano Ermon, Christopher D Manning, and Chelsea Finn · 2023
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GitHub Copilot now has a better AI model and new capabilities
Shuyin Zhao · 2023
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