--- title: "Who cites End-to-End Differentiable Proving — 75 citing papers" description: "75 papers of the Elamur Research library cite «End-to-End Differentiable Proving», found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/papers/rocktaschel-2017-end-end-differentiable-proving/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/rocktaschel-2017-end-end-differentiable-proving/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [End-to-End Differentiable Proving](https://md.research.elamur.ai/free/en/papers/rocktaschel-2017-end-end-differentiable-proving/) / cited by # Who cites «End-to-End Differentiable Proving» 75 papers of our library cite it (of the 149,439 whose bibliographies we read) · 19 with a page here, the most cited first · [← back to «End-to-End Differentiable Proving»](https://md.research.elamur.ai/free/en/papers/rocktaschel-2017-end-end-differentiable-proving/) 1. **[FEVER: a Large-scale Dataset for Fact Extraction and VERification](https://md.research.elamur.ai/free/en/papers/thorne-2018-fever-large-scale-dataset-fact/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**James Thorne, Andreas Vlachos, Christos Christodoulopoulos, et al.*2018 · 2,221 citations* 2. **[Knowledge Graphs](https://md.research.elamur.ai/free/en/papers/hogan-2020-knowledge-graphs/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Aidan Hogan, Eva Blomqvist, Michael Cochez, et al.*2020 · 2,014 citations* 3. [**RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space arXiv:1902.10197**Zhiqing Sun, Zhi-Hong Deng, Jian-Yun Nie, et al.*2019 · 1,073 citations*](https://md.research.elamur.ai/free/en/papers/sun-2019-rotate-knowledge-graph-embedding-relational/) 4. [**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/) 5. **[ProofWriter: Generating Implications, Proofs, and Abductive Statements over Natural Language](https://md.research.elamur.ai/free/en/papers/tafjord-2021-proofwriter-generating-implications-proofs-abductive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Oyvind Tafjord, Bhavana Dalvi, Peter Clark*2021 · 335 citations* 6. **[Logic Tensor Networks](https://md.research.elamur.ai/free/en/papers/badreddine-2020-logic-tensor-networks/) [Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/artificial-intelligence/)**Samy Badreddine, Artur d'Avila Garcez, Luciano Serafini, et al.*2020 · 276 citations* 7. [**Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought arXiv:2210.01240**Abulhair Saparov, He He*2022 · 244 citations*](https://md.research.elamur.ai/free/en/papers/saparov-2022-language-models-greedy-reasoners-systematic/) 8. [**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/) 9. **[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* 10. [**GamePad: A Learning Environment for Theorem Proving arXiv:1806.00608**Daniel Huang, Prafulla Dhariwal, Dawn Song, et al.*2018 · 94 citations*](https://md.research.elamur.ai/free/en/papers/huang-2018-gamepad-learning-environment-theorem-proving/) 11. [**Learning to Prove Theorems via Interacting with Proof Assistants arXiv:1905.09381**Kaiyu Yang, Jia Deng*2019 · 90 citations*](https://md.research.elamur.ai/free/en/papers/yang-2019-learning-prove-theorems-interacting-proof/) 12. [**Complex Query Answering with Neural Link Predictors arXiv:2011.03459**Erik Arakelyan, Daniel Daza, Pasquale Minervini, et al.*2020 · 61 citations*](https://md.research.elamur.ai/free/en/papers/arakelyan-2020-complex-query-answering-neural-link/) 13. [**INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving arXiv:2007.02924**Yuhuai Wu, Albert Qiaochu Jiang, Jimmy Ba, et al.*2020 · 41 citations*](https://md.research.elamur.ai/free/en/papers/wu-2020-int-inequality-benchmark-evaluating-generalization/) 14. [**TILP: Differentiable Learning of Temporal Logical Rules on Knowledge Graphs arXiv:2402.12309**Siheng Xiong, Yuan Yang, Faramarz Fekri, et al.*2024 · 25 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2024-tilp-differentiable-learning-temporal-logical/) 15. [**TacticZero: Learning to Prove Theorems from Scratch with Deep Reinforcement Learning arXiv:2102.09756**Minchao Wu, Michael Norrish, Christian Walder, et al.*2021 · 24 citations*](https://md.research.elamur.ai/free/en/papers/wu-2021-tacticzero-learning-prove-theorems-scratch/) 16. [**Certified Deductive Reasoning with Language Models arXiv:2306.04031**Gabriel Poesia, Kanishk Gandhi, Eric Zelikman, et al.*2023 · 23 citations*](https://md.research.elamur.ai/free/en/papers/poesia-2023-certified-deductive-reasoning-language-models/) 17. [**Neurosymbolic AI: The 3rd Wave arXiv:2012.05876**Artur d'Avila Garcez, Luis C. Lamb*2020 · 20 citations*](https://md.research.elamur.ai/free/en/papers/garcez-2020-neurosymbolic-ai-3rd-wave/) 18. [**Learning Iterative Reasoning through Energy Diffusion arXiv:2406.11179**Yilun Du, Jiayuan Mao, Joshua B. Tenenbaum*2024 · 11 citations*](https://md.research.elamur.ai/free/en/papers/du-2024-learning-iterative-reasoning-through-energy/) 19. [**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/) 56 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/rocktaschel-2017-end-end-differentiable-proving/) — End-to-End Differentiable Proving