aicpp
Neuro-symbolic program synthesis for structured reasoning
Citation
@article{colelough2025neurosymbolic,
title = {Neuro-Symbolic {AI} in 2024: A Systematic Review},
author = {Colelough, B. C. and others},
journal = {arXiv preprint arXiv:2501.05435},
year = {2025}
}
@inproceedings{mao2019neuro,
title = {The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences from Natural Supervision},
author = {Mao, Jiayuan and Gan, Chuang and Kohli, Pushmeet and Tenenbaum, Joshua B. and Wu, Jiajun},
booktitle = {International Conference on Learning Representations (ICLR)},
year = {2019}
}
@inproceedings{schlichtkrull2018modeling,
title = {Modeling Relational Data with Graph Convolutional Networks},
author = {Schlichtkrull, Michael and Kipf, Thomas N. and Bloem, Peter and Van Den Berg, Rianne and Titov, Ivan and Welling, Max},
booktitle = {European Semantic Web Conference (ESWC)},
year = {2018}
}
@inproceedings{gulwani2011automating,
title = {Automating String Processing in Spreadsheets Using Input-Output Examples},
author = {Gulwani, Sumit},
booktitle = {ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages (POPL)},
year = {2011}
}
@article{chen2021evaluating,
title = {Evaluating Large Language Models Trained on Code},
author = {Chen, Mark and others},
journal = {arXiv preprint arXiv:2107.03374},
year = {2021}
}
@inproceedings{bunel2017learning,
title = {Learning to Superoptimize Programs},
author = {Bunel, Rudy and Desmaison, Alban and Kohli, Pushmeet and Torr, Philip H. S. and Kumar, M. Pawan},
booktitle = {International Conference on Learning Representations (ICLR)},
year = {2017}
}
@inproceedings{zaremba2015learning,
title = {Learning to Execute},
author = {Zaremba, Wojciech and Sutskever, Ilya},
booktitle = {International Conference on Learning Representations (ICLR)},
year = {2015}
}
@article{chollet2019measure,
title = {On the Measure of Intelligence},
author = {Chollet, Fran\c{c}ois},
journal = {arXiv preprint arXiv:1911.01547},
year = {2019}
}
@misc{hodel2024arc,
title = {{ARC-AGI} with Program Synthesis},
author = {Hodel, Michael},
howpublished = {\url{https://github.com/michaelhodel/arc-dsl}},
year = {2024}
}
@article{lezoche2020cyber,
title = {Cyber-Physical Systems, a new formal paradigm to model redundancy and resiliency},
author = {Lezoche, Mario and Panetto, Herv{\'e}},
journal = {Enterprise Information Systems},
year = {2020}
}
@inproceedings{ellis2021dreamcoder,
title = {{DreamCoder}: Bootstrapping Inductive Program Synthesis with Wake-Sleep Library Learning},
author = {Ellis, Kevin and Wong, Catherine and Nye, Maxwell and Sable-Meyer, Mathieu and Cary, Luc and Morales, Lucas and Hewitt, Luke and Solar-Lezama, Armando and Tenenbaum, Joshua B.},
booktitle = {ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI)},
year = {2021}
}
@inproceedings{bowers2023stitch,
title = {Top-Down Synthesis for Library Learning},
author = {Bowers, Matthew and Olausson, Theo X. and Wong, Celine and Grand, Gabriel and Tenenbaum, Joshua B. and Ellis, Kevin and Solar-Lezama, Armando},
booktitle = {ACM SIGPLAN Symposium on Principles of Programming Languages (POPL)},
year = {2023}
}
Related work
aicpp is related to research on:
- neuro-symbolic reasoning
- program synthesis
- ARC-AGI
- neural-guided search
- executable DSLs