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Program synthesis aims to automatically construct human-readable programs that satisfy given task specifications, such as input/output pairs or demonstrations.
Alex Graves, Greg Wayne, and Ivo Danihelka · 2014
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Neural programmer: Inducing latent programs with gradient descent
Arvind Neelakantan, Quoc V Le, and Ilya Sutskever · 2015
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Neural gpus learn algorithms
Łukasz Kaiser and Ilya Sutskever · 2016
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Neural programmer-interpreters
Scott Reed and Nando De Freitas · 2016
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Learning simple algorithms from examples
Wojciech Zaremba, Tomas Mikolov, Armand Joulin, and Rob Fergus · 2016
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Deepcoder: Learning to write programs
Matej Balog, Alexander L Gaunt, Marc Brockschmidt, Sebastian Nowozin, and Daniel Tarlow · 2017
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Programming with a differentiable forth interpreter
Matko Bošnjak, Tim Rocktäschel, Jason Naradowsky, and Sebastian Riedel · 2017
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Making neural programming architectures generalize via recursion
Jonathon Cai, Richard Shin, and Dawn Song · 2017
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Differentiable programs with neural libraries
Alexander L. Gaunt, Marc Brockschmidt, Nate Kushman, and Daniel Tarlow · 2017
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Neuro-symbolic program synthesis
Emilio Parisotto, Abdel-rahman Mohamed, Rishabh Singh, Lihong Li, Dengyong Zhou, and Pushmeet Kohli · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Neural scene de-rendering
Jiajun Wu, Joshua B Tenenbaum, and Pushmeet Kohli · 2017
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Neural program synthesis with priority queue training
Daniel A Abolafia, Mohammad Norouzi, Jonathan Shen, Rui Zhao, and Quoc V Le · 2018
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Leveraging grammar and reinforcement learning for neural program synthesis
Rudy R Bunel, Matthew Hausknecht, Jacob Devlin, Rishabh Singh, and Pushmeet Kohli · 2018
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Nl2bash: A corpus and semantic parser for natural language interface to the linux operating system
Xi Victoria Lin, Chenglong Wang, Luke Zettlemoyer, and Michael D Ernst · 2018
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Improving neural program synthesis with inferred execution traces
Eui Chul Shin, Illia Polosukhin, and Dawn Song · 2018
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Neural program synthesis from diverse demonstration videos
Shao-Hua Sun, Hyeonwoo Noh, Sriram Somasundaram, and Joseph Lim · 2018
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Programmatically interpretable reinforcement learning
Abhinav Verma, Vijayaraghavan Murali, Rishabh Singh, Pushmeet Kohli, and Swarat Chaudhuri · 2018
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Improving the universality and learnability of neural programmer-interpreters with combinator abstraction
Learning compositional neural programs with recursive tree search and planning
Thomas Pierrot, Guillaume Ligner, Scott E Reed, Olivier Sigaud, Nicolas Perrin, Alexandre Laterre, David Kas, Karim Beguir, and Nando de Freitas · 2019
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Dreamcoder: Growing generalizable, interpretable knowledge with wake-sleep bayesian program learning
Kevin Ellis, Catherine Wong, Maxwell Nye, Mathias Sable-Meyer, Luc Cary, Lucas Morales, Luke Hewitt, Armando Solar-Lezama, and Joshua B Tenenbaum · 2020
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Program synthesis as latent continuous optimization: Evolutionary search in neural embeddings
Paweł Liskowski, Krzysztof Krawiec, Nihat Engin Toklu, and Jerry Swan · 2020
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Few-shot bayesian imitation learning with logical program policies
Tom Silver, Kelsey R Allen, Alex K Lew, Leslie Pack Kaelbling, and Josh Tenenbaum · 2020
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Program guided agent
Shao-Hua Sun, Te-Lin Wu, and Joseph J. Lim · 2020
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Da Xiao, Jo-Yu Liao, and Xingyuan Yuan · 2018
Cited alongside, same era.
Neural task programming: Learning to generalize across hierarchical tasks
Danfei Xu, Suraj Nair, Yuke Zhu, Julian Gao, Animesh Garg, Li Fei-Fei, and Silvio Savarese · 2018
Cited alongside, same era.
From explanation to synthesis: Compositional program induction for learning from demonstration
Michael Burke, Svetlin Penkov, and Subramanian Ramamoorthy · 2019
Cited alongside, same era.
Execution-guided neural program synthesis
Xinyun Chen, Chang Liu, and Dawn Song · 2019
Cited alongside, same era.
Write, execute, assess: Program synthesis with a repl
Kevin Ellis, Maxwell Nye, Yewen Pu, Felix Sosa, Josh Tenenbaum, and Armando Solar-Lezama · 2019
Cited alongside, same era.
Beyond imitation: Zero-shot task transfer on robots by learning concepts as cognitive programs
Miguel Lázaro-Gredilla, Dianhuan Lin, J Swaroop Guntupalli, and Dileep George · 2019
Cited alongside, same era.
Synthesizing environment-aware activities via activity sketches
Yuan-Hong Liao, Xavier Puig, Marko Boben, Antonio Torralba, and Sanja Fidler · 2019
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, Alex Ray, Raul Puri, Gretchen Krueger, Michael Petrov, Heidy Khlaaf, Girish Sastry, Pamela Mishkin, Brooke Chan, Scott Gray, Nick Ryder, Mikhail Pavlov, Alethea Power, Lukasz Kaiser, Mohammad Bavarian, Clemens Winter, Philippe Tillet, Felipe Petroski Such, Dave Cummings, Matthias Plappert, Fotios Chantzis, Elizabeth Barnes, Ariel Herbert-Voss, William Hebgen Guss, Alex Nichol, Alex Paino, Nikolas Tezak, Jie Tang, Igor Babuschkin, Suchir Balaji, Shantanu Jain, William Saunders, Christopher Hesse, Andrew N. Carr, Jan Leike, Josh Achiam, Vedant Misra, Evan Morikawa, Alec Radford, Matthew Knight, Miles Brundage, Mira Murati, Katie Mayer, Peter Welinder, Bob McGrew, Dario Amodei, Sam McCandlish, Ilya Sutskever, and Wojciech Zaremba · 2021
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Latent programmer: Discrete latent codes for program synthesis
Joey Hong, David Dohan, Rishabh Singh, Charles Sutton, and Manzil Zaheer · 2021
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Bustle: Bottom-up program synthesis through learning-guided exploration
Augustus Odena, Kensen Shi, David Bieber, Rishabh Singh, Charles Sutton, and Hanjun Dai · 2021
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Learning to synthesize programs as interpretable and generalizable policies
Dweep Trivedi, Jesse Zhang, Shao-Hua Sun, and Joseph J Lim · 2021
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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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A conversational paradigm for program synthesis
Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, and Caiming Xiong · 2022
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Compositional generalization and decomposition in neural program synthesis
Kensen Shi, Joey Hong, Manzil Zaheer, Pengcheng Yin, and Charles Sutton · 2022
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Hierarchical programmatic reinforcement learning via learning to compose programs
Guan-Ting Liu, En-Pei Hu, Pu-Jen Cheng, Hung-Yi Lee, and Shao-Hua Sun · 2023
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