--- title: "Who cites Programming with a Differentiable Forth Interpreter" description: "27 papers of the Elamur Research library cite «Programming with a Differentiable Forth Interpreter», found in their bibliographies; the most…" canonical: "https://research.elamur.ai/free/en/papers/bosnjak-2016-programming-differentiable-forth-interpreter/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/bosnjak-2016-programming-differentiable-forth-interpreter/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Programming with a Differentiable Forth…](https://md.research.elamur.ai/free/en/papers/bosnjak-2016-programming-differentiable-forth-interpreter/) / cited by # Who cites «Programming with a Differentiable Forth Interpreter» 27 papers of our library cite it (of the 149,439 whose bibliographies we read) · 13 with a page here, the most cited first · [← back to «Programming with a Differentiable Forth Interpreter»](https://md.research.elamur.ai/free/en/papers/bosnjak-2016-programming-differentiable-forth-interpreter/) 1. [**Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models arXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj**Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.*2022 · 1,756 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2022-imitation-game-quantifying-extrapolating-capabilities/) 2. [**TabFact: A Large-scale Dataset for Table-based Fact Verification arXiv:1909.02164**Wenhu Chen, Hongmin Wang, Jianshu Chen, et al.*2019 · 515 citations*](https://md.research.elamur.ai/free/en/papers/chen-2019-tabfact-large-scale-dataset-table/) 3. [**Deep Learning: A Critical Appraisal arXiv:1801.00631**Gary Marcus*2018 · 417 citations*](https://md.research.elamur.ai/free/en/papers/marcus-2018-deep-learning-critical-appraisal/) 4. **[From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood](https://md.research.elamur.ai/free/en/papers/guu-2017-language-programs-bridging-reinforcement-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kelvin Guu, Panupong Pasupat, Evan Liu, et al.*2017 · 236 citations* 5. [**End-to-End Differentiable Proving arXiv:1705.11040**Tim Rocktäschel, Sebastian Riedel*2017 · 188 citations*](https://md.research.elamur.ai/free/en/papers/rocktaschel-2017-end-end-differentiable-proving/) 6. [**DeepProbLog: Neural Probabilistic Logic Programming arXiv:1805.10872**Robin Manhaeve, Sebastijan Dumančić, Angelika Kimmig, et al.*2018 · 172 citations*](https://md.research.elamur.ai/free/en/papers/manhaeve-2018-deepproblog-neural-probabilistic-logic/) 7. **[A Survey of Machine Learning for Big Code and Naturalness](https://md.research.elamur.ai/free/en/papers/allamanis-2017-survey-machine-learning-big-code/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Miltiadis Allamanis, Earl T. Barr, Premkumar Devanbu, et al.*2017 · 167 citations* 8. [**Neuro-Symbolic Program Synthesis arXiv:1611.01855**Emilio Parisotto, Abdel-rahman Mohamed, Rishabh Singh, et al.*2016 · 152 citations*](https://md.research.elamur.ai/free/en/papers/parisotto-2016-neuro-symbolic-program-synthesis/) 9. [**Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis arXiv:1805.04276**Rudy Bunel, Matthew Hausknecht, Jacob Devlin, et al.*2018 · 66 citations*](https://md.research.elamur.ai/free/en/papers/bunel-2018-leveraging-grammar-reinforcement-learning-neural/) 10. [**Program Synthesis Foundations and Trends in Programming Languages 4(1-2)**Sumit Gulwani, Oleksandr Polozov, Rishabh Singh*2017 · 63 citations*](https://md.research.elamur.ai/free/en/papers/gulwani-2017-program-synthesis/) 11. [**Learning to Infer Program Sketches arXiv:1902.06349**Maxwell Nye, Luke Hewitt, Joshua Tenenbaum, et al.*2019 · 53 citations*](https://md.research.elamur.ai/free/en/papers/nye-2019-learning-infer-program-sketches/) 12. [**NExT: Teaching Large Language Models to Reason about Code Execution arXiv:2404.14662**Ansong Ni, Miltiadis Allamanis, Arman Cohan, et al.*2024 · 30 citations*](https://md.research.elamur.ai/free/en/papers/ni-2024-next-teaching-large-language-models/) 13. [**From Statistical Relational to Neurosymbolic Artificial Intelligence: a Survey arXiv:2108.11451**Giuseppe Marra, Sebastijan Dumančić, Robin Manhaeve, et al.*2021 · 3 citations*](https://md.research.elamur.ai/free/en/papers/marra-2021-statistical-relational-neurosymbolic-artificial/) 14 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/bosnjak-2016-programming-differentiable-forth-interpreter/) — Programming with a Differentiable Forth Interpreter