aicpp

Neuro-symbolic program synthesis for structured reasoning

Paper PDF

Source

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}
}

aicpp is related to research on:

  • neuro-symbolic reasoning
  • program synthesis
  • ARC-AGI
  • neural-guided search
  • executable DSLs