--- title: "Who cites Learning a SAT Solver from Single-Bit Supervision" description: "56 papers of the Elamur Research library cite «Learning a SAT Solver from Single-Bit Supervision», found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/papers/selsam-2018-learning-sat-solver-single-bit/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/selsam-2018-learning-sat-solver-single-bit/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Learning a SAT Solver from Single-Bit Supervision](https://md.research.elamur.ai/free/en/papers/selsam-2018-learning-sat-solver-single-bit/) / cited by # Who cites «Learning a SAT Solver from Single-Bit Supervision» 56 papers of our library cite it (of the 149,439 whose bibliographies we read) · 12 with a page here, the most cited first · [← back to «Learning a SAT Solver from Single-Bit Supervision»](https://md.research.elamur.ai/free/en/papers/selsam-2018-learning-sat-solver-single-bit/) 1. [**Relational inductive biases, deep learning, and graph networks arXiv:1806.01261**Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, et al.*2018 · 2,335 citations*](https://md.research.elamur.ai/free/en/papers/battaglia-2018-relational-inductive-biases-deep-learning/) 2. [**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/) 3. [**Evaluating Models' Local Decision Boundaries via Contrast Sets**Matt Gardner, Yoav Artzi, Victoria Basmov, et al.*2020 · 531 citations*](https://md.research.elamur.ai/free/en/papers/gardner-2020-evaluating-models-local-decision-boundaries/) 4. **[Transformers as Soft Reasoners over Language](https://md.research.elamur.ai/free/en/papers/clark-2020-transformers-soft-reasoners-over-language/) [International Joint Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/international-joint-conference-on-artificial-intelligence/)**Peter Clark, Oyvind Tafjord, Kyle Richardson*2020 · 382 citations* 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. [**Analysing Mathematical Reasoning Abilities of Neural Models arXiv:1904.01557**David Saxton, Edward Grefenstette, Felix Hill, et al.*2019 · 288 citations*](https://md.research.elamur.ai/free/en/papers/saxton-2019-analysing-mathematical-reasoning-abilities-neural/) 7. [**Generative Language Modeling for Automated Theorem Proving arXiv:2009.03393**Stanislas Polu, Ilya Sutskever*2020 · 241 citations*](https://md.research.elamur.ai/free/en/papers/polu-2020-generative-language-modeling-automated-theorem/) 8. **[What Can Transformers Learn In-Context? A Case Study of Simple Function Classes](https://md.research.elamur.ai/free/en/papers/garg-2022-transformers-learn-context-case-study/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shivam Garg, Dimitris Tsipras, Percy Liang, et al.*2022 · 209 citations* 9. [**Formal Mathematics Statement Curriculum Learning arXiv:2202.01344**Stanislas Polu, Jesse Michael Han, Kunhao Zheng, et al.*2022 · 133 citations*](https://md.research.elamur.ai/free/en/papers/polu-2022-formal-mathematics-statement-curriculum-learning/) 10. **[PRover: Proof Generation for Interpretable Reasoning over Rules](https://md.research.elamur.ai/free/en/papers/saha-2020-prover-proof-generation-interpretable-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Swarnadeep Saha, Sayan Ghosh, Shashank Srivastava, et al.*2020 · 103 citations* 11. **[SATQuest: A Verifier for Logical Reasoning Evaluation and Reinforcement Fine-Tuning of LLMs](https://md.research.elamur.ai/free/en/papers/zhao-2026-satquest-verifier-logical-reasoning-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yanxiao Zhao, Yaqian Li, Zihao Bo, et al.*2026* 12. **[Methods for Constraint Solving Problems Based on Learn to Reason Model: A Review (基于学习-推理的约束求解方法研究进展)](https://md.research.elamur.ai/free/en/papers/zou-2023-methods-constraint-solving/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yue Zou (邹悦), Jiayang Lai (赖家洋), Yonggang Zhang (张永刚)*2023* 44 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/selsam-2018-learning-sat-solver-single-bit/) — Learning a SAT Solver from Single-Bit Supervision