--- title: "Who cites INT: An Inequality Benchmark for — 33 citing papers" description: "33 papers of the Elamur Research library cite «INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving», found in their…" canonical: "https://research.elamur.ai/free/en/papers/wu-2020-int-inequality-benchmark-evaluating-generalization/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/wu-2020-int-inequality-benchmark-evaluating-generalization/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [INT: An Inequality Benchmark for Evaluating…](https://md.research.elamur.ai/free/en/papers/wu-2020-int-inequality-benchmark-evaluating-generalization/) / cited by # Who cites «INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving» 33 papers of our library cite it (of the 149,439 whose bibliographies we read) · 24 with a page here, the most cited first · [← back to «INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving»](https://md.research.elamur.ai/free/en/papers/wu-2020-int-inequality-benchmark-evaluating-generalization/) 1. [**On the Opportunities and Risks of Foundation Models arXiv:2108.07258**Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.*2021 · 3,160 citations*](https://md.research.elamur.ai/free/en/papers/bommasani-2021-opportunities-risks-foundation-models/) 2. [**MiniF2F: a cross-system benchmark for formal Olympiad-level mathematics arXiv:2109.00110**Kunhao Zheng, Jesse Michael Han, Stanislas Polu*2021 · 257 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2021-minif2f-cross-system-benchmark-formal/) 3. [**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/) 4. [**Autoformalization with Large Language Models arXiv:2205.12615**Yuhuai Wu, Albert Q. Jiang, Wenda Li, et al.*2022 · 204 citations*](https://md.research.elamur.ai/free/en/papers/wu-2022-autoformalization-large-language-models/) 5. **[LILA: A Unified Benchmark for Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/mishra-2022-lila-unified-benchmark-mathematical-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Swaroop Mishra, Matthew Finlayson, Pan Lu, et al.*2022 · 179 citations* 6. [**Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs arXiv:2210.12283**Albert Q. Jiang, Sean Welleck, Jin Peng Zhou, et al.*2022 · 178 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2022-draft-sketch-prove-guiding-formal/) 7. [**Exploring Length Generalization in Large Language Models arXiv:2207.04901**Cem Anil, Yuhuai Wu, Anders Andreassen, et al.*2022 · 139 citations*](https://md.research.elamur.ai/free/en/papers/anil-2022-exploring-length-generalization-large-language/) 8. [**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/) 9. [**DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data arXiv:2405.14333**Huajian Xin, Daya Guo, Zhihong Shao, et al.*2024 · 111 citations*](https://md.research.elamur.ai/free/en/papers/xin-2024-deepseek-prover-advancing-theorem-proving/) 10. **[Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples](https://md.research.elamur.ai/free/en/papers/saparov-2023-testing-general-deductive-reasoning-capacity/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Abulhair Saparov, Richard Yuanzhe Pang, Vishakh Padmakumar, et al.*2023 · 84 citations* 11. [**LEGO-Prover: Neural Theorem Proving with Growing Libraries arXiv:2310.00656**Haiming Wang, Huajian Xin, Chuanyang Zheng, et al.*2023 · 79 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-lego-prover-neural-theorem-proving/) 12. [**Formal Mathematical Reasoning: A New Frontier in AI arXiv:2412.16075**Kaiyu Yang, Gabriel Poesia, Jingxuan He, et al.*2024 · 49 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-formal-mathematical-reasoning-new-frontier/) 13. [**A Survey on Deep Learning for Theorem Proving arXiv:2404.09939**Zhaoyu Li, Jialiang Sun, Logan Murphy, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-survey-deep-learning-theorem-proving/) 14. [**STP: Self-play LLM Theorem Provers with Iterative Conjecturing and Proving arXiv:2502.00212**Kefan Dong, Tengyu Ma*2025 · 43 citations*](https://md.research.elamur.ai/free/en/papers/dong-2025-stp-self-play-llm-theorem/) 15. [**IsarStep: a Benchmark for High-level Mathematical Reasoning arXiv:2006.09265**Wenda Li, Lei Yu, Yuhuai Wu, et al.*2020 · 43 citations*](https://md.research.elamur.ai/free/en/papers/li-2020-isarstep-benchmark-high-level-mathematical/) 16. **[DT-Solver: Automated Theorem Proving with Dynamic-Tree Sampling Guided by Proof-level Value Function](https://md.research.elamur.ai/free/en/papers/wang-2023-dt-solver-automated-theorem-proving/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haiming Wang, Ye Yuan, Zhengying Liu, et al.*2023 · 40 citations* 17. [**LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning arXiv:2101.06223**Yuhuai Wu, Markus Rabe, Wenda Li, et al.*2021 · 39 citations*](https://md.research.elamur.ai/free/en/papers/wu-2021-lime-learning-inductive-bias-primitives/) 18. [**MUSTARD: Mastering Uniform Synthesis of Theorem and Proof Data arXiv:2402.08957 (ICLR 2024 spotlight)**Yinya Huang, Xiaohan Lin, Zhengying Liu, et al.*2024 · 29 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-mustard-mastering-uniform-synthesis-theorem/) 19. [**Lyra: Orchestrating Dual Correction in Automated Theorem Proving arXiv:2309.15806**Chuanyang Zheng, Haiming Wang, Enze Xie, et al.*2023 · 24 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2023-lyra-orchestrating-dual-correction-automated/) 20. [**Teaching Temporal Logics to Neural Networks arXiv:2003.04218**Christopher Hahn, Frederik Schmitt, Jens U. Kreber, et al.*2020 · 24 citations*](https://md.research.elamur.ai/free/en/papers/hahn-2020-teaching-temporal-logics-neural-networks/) 21. **[TRIGO: Benchmarking Formal Mathematical Proof Reduction for Generative Language Models](https://md.research.elamur.ai/free/en/papers/xiong-2023-trigo-benchmarking-formal-mathematical-proof/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jing Xiong, Jianhao Shen, Ye Yuan, et al.*2023 · 21 citations* 22. **[A Symbolic Framework for Evaluating Mathematical Reasoning and Generalisation with Transformers](https://md.research.elamur.ai/free/en/papers/meadows-2024-symbolic-framework-evaluating-mathematical-reasoning/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jordan Meadows, Marco Valentino, Damien Teney, et al.*2024 · 14 citations* 23. **[Proving Olympiad Algebraic Inequalities without Human Demonstrations](https://md.research.elamur.ai/free/en/papers/wei-2024-proving-olympiad-algebraic-inequalities-without/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Chenrui Wei, Mengzhou Sun, Wei Wang*2024 · 12 citations* 24. [**Proving Olympiad Inequalities by Synergizing LLMs and Symbolic Reasoning arXiv:2502.13834**Zenan Li, Zhaoyu Li, Wen Tang, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-proving-olympiad-inequalities-synergizing-llms/) 9 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/wu-2020-int-inequality-benchmark-evaluating-generalization/) — INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving