Built on

Gers, Felix A., Jürgen Schmidhuber, and Fred Cummins. "Learning to forget: Continual prediction with LSTM." Neural computation 12.10 (2000): 2451-2471
2000
Earlier work this paper cites.
Lafferty, John, Andrew McCallum, and Fernando Pereira. "Conditional random fields: Probabilistic models for segmenting and labeling sequence data." Proceedings of the eighteenth international conference on machine learning, ICML. Vol. 1. 2001
Original
2001
Earlier work this paper cites.
Carpenter, Bob. "Scaling high-order character language models to gigabytes." Proceedings of the Workshop on Software. Association for Computational Linguistics, 2005
2005
Earlier work this paper cites.
Singh, Rishabh, Sumit Gulwani, and Armando Solar-Lezama. "Automated feedback generation for introductory programming assignments." ACM SIGPLAN Notices 48.6 (2013): 15-26
2013
Earlier work this paper cites.
Mikolov, Tomas, et al. "Distributed representations of words and phrases and their compositionality." Advances in neural information processing systems. 2013
2013
Earlier work this paper cites.

Similar

Mikolov, Tomas, et al. "Distributed representations of words and phrases and their compositionality." Advances in neural information processing systems. 2013
2013
Cited alongside, same era.
Raychev, Veselin, Martin Vechev, and Eran Yahav. "Code completion with statistical language models." ACM SIGPLAN Notices. Vol. 49. No. 6. ACM, 2014
2014
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Pennington, Jeffrey, Richard Socher, and Christopher D. Manning. "Glove: Global Vectors for Word Representation." EMNLP. Vol. 14. 2014
2014
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Cho, Kyunghyun, et al. "Learning phrase representations using RNN encoder-decoder for statistical machine translation." arXiv preprint arXiv:1406.1078 (2014)
Original
2014
Cited alongside, same era.
Kiros, Ryan, et al. "Skip-thought vectors." Advances in Neural Information Processing Systems. 2015
2015

Then

Raychev, Veselin, Martin Vechev, and Andreas Krause. "Predicting program properties from big code." ACM SIGPLAN Notices. Vol. 50. No. 1. ACM, 2015
2015
Later among the works it cites.
Long, Fan, and Martin Rinard. "Automatic patch generation by learning correct code." ACM SIGPLAN Notices. Vol. 51. No. 1. ACM, 2016
2016
Closest in time.
Gulwani, Sumit, Ivan Radicek, and Florian Zuleger. "Automated Clustering and Program Repair for Introductory Programming Assignments." arXiv preprint arXiv:1603.03165 (2016)
Original
2016
Closest in time.
Singh, Gursimran, Shashank Srikant, and Varun Aggarwal. "Question Independent Grading using Machine Learning: The Case of Computer Program Grading."
2016
Closest in time.
Abadi, Martın, et al. "Tensorflow: Large-scale machine learning on heterogeneous distributed systems." arXiv preprint arXiv:1603.04467 (2016). APA

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2016

sk_p: a neural program corrector for MOOCs

Pu, Yewen, Narasimhan, Karthik, Solar-Lezama, Armando et al.

Understand

We present a novel technique for automatic program correction in MOOCs, capable of fixing both syntactic and semantic errors without manual, problem specific correction strategies.

Given an incorrect student program, it generates candidate programs from a distribution of likely corrections, and checks each candidate for correctness against a test suite.
The key observation is that in MOOCs many programs share similar code fragments, and the seq2seq neural network model, used in the natural-language processing task of machine translation, can be modified and trained to recover these fragments.
Experiment shows our scheme can correct 29% of all incorrect submissions and out-performs state of the art approach which requires manual, problem specific correction strategies.

Built on

Gers, Felix A., Jürgen Schmidhuber, and Fred Cummins. "Learning to forget: Continual prediction with LSTM." Neural computation 12.10 (2000): 2451-2471
2000
Earlier work this paper cites.
Lafferty, John, Andrew McCallum, and Fernando Pereira. "Conditional random fields: Probabilistic models for segmenting and labeling sequence data." Proceedings of the eighteenth international conference on machine learning, ICML. Vol. 1. 2001
Original
2001
Earlier work this paper cites.
Carpenter, Bob. "Scaling high-order character language models to gigabytes." Proceedings of the Workshop on Software. Association for Computational Linguistics, 2005
2005
Earlier work this paper cites.
Singh, Rishabh, Sumit Gulwani, and Armando Solar-Lezama. "Automated feedback generation for introductory programming assignments." ACM SIGPLAN Notices 48.6 (2013): 15-26
2013
Earlier work this paper cites.
Mikolov, Tomas, et al. "Distributed representations of words and phrases and their compositionality." Advances in neural information processing systems. 2013
2013
Earlier work this paper cites.

Similar

Mikolov, Tomas, et al. "Distributed representations of words and phrases and their compositionality." Advances in neural information processing systems. 2013
2013
Cited alongside, same era.
Raychev, Veselin, Martin Vechev, and Eran Yahav. "Code completion with statistical language models." ACM SIGPLAN Notices. Vol. 49. No. 6. ACM, 2014
2014
Cited alongside, same era.
Pennington, Jeffrey, Richard Socher, and Christopher D. Manning. "Glove: Global Vectors for Word Representation." EMNLP. Vol. 14. 2014
2014
Cited alongside, same era.
Cho, Kyunghyun, et al. "Learning phrase representations using RNN encoder-decoder for statistical machine translation." arXiv preprint arXiv:1406.1078 (2014)
Original
2014
Cited alongside, same era.
Kiros, Ryan, et al. "Skip-thought vectors." Advances in Neural Information Processing Systems. 2015
2015

Then

Raychev, Veselin, Martin Vechev, and Andreas Krause. "Predicting program properties from big code." ACM SIGPLAN Notices. Vol. 50. No. 1. ACM, 2015
2015
Later among the works it cites.
Long, Fan, and Martin Rinard. "Automatic patch generation by learning correct code." ACM SIGPLAN Notices. Vol. 51. No. 1. ACM, 2016
2016
Closest in time.
Gulwani, Sumit, Ivan Radicek, and Florian Zuleger. "Automated Clustering and Program Repair for Introductory Programming Assignments." arXiv preprint arXiv:1603.03165 (2016)
Original
2016
Closest in time.
Singh, Gursimran, Shashank Srikant, and Varun Aggarwal. "Question Independent Grading using Machine Learning: The Case of Computer Program Grading."
2016
Closest in time.
Abadi, Martın, et al. "Tensorflow: Large-scale machine learning on heterogeneous distributed systems." arXiv preprint arXiv:1603.04467 (2016). APA

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alphaXiv searches the wider corpus for related work and actual follow-ups.

Open on alphaXiv

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Cited alongside, same era.

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Cited in the paper.

Original

2016

Closest in time.