🔗 Who cites «Deep Learning for Symbolic Mathematics»

93 papers of our library cite it (of the 149,439 whose bibliographies we read) · 21 with a page here, the most cited first · ← back to «Deep Learning for Symbolic Mathematics»

1. Training Verifiers to Solve Math Word ProblemsarXiv:2110.14168Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, et al.2021 · 3,796 citations
2. Measuring Mathematical Problem Solving With the MATH DatasetarXiv:2103.03874Dan Hendrycks, Collin Burns, Saurav Kadavath, et al.2021 · 2,395 citations
3. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelsarXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5BvosjAarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.2022 · 1,756 citations
4. AudioLM: a Language Modeling Approach to Audio GenerationIEEE/ACM Transactions on Audio Speech and Language ProcessingZalan Borsos, Raphael Marinier, Damien Vincent, et al.2022 · 581 citations
5. Mathematical Capabilities of ChatGPTConference on Neural Information Processing Systems (NeurIPS)Simon Frieder, Luca Pinchetti, Alexis Chevalier, et al.2023 · 449 citations
6. Transformers as Soft Reasoners over LanguageInternational Joint Conference on Artificial IntelligencePeter Clark, Oyvind Tafjord, Kyle Richardson2020 · 382 citations
7. The Next Decade in AI: Four Steps Towards Robust Artificial IntelligencearXiv:2002.06177Gary Marcus2020 · 332 citations
8. Injecting Numerical Reasoning Skills into Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Mor Geva, Ankit Gupta, Jonathan Berant2020 · 269 citations
9. Generative Language Modeling for Automated Theorem ProvingarXiv:2009.03393Stanislas Polu, Ilya Sutskever2020 · 241 citations
10. Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal ProofsarXiv:2210.12283Albert Q. Jiang, Sean Welleck, Jin Peng Zhou, et al.2022 · 178 citations
11. HyperTree Proof Search for Neural Theorem ProvingConference on Neural Information Processing Systems (NeurIPS)Guillaume Lample, Marie-Anne Lachaux, Thibaut Lavril, et al.2022 · 151 citations
12. PRover: Proof Generation for Interpretable Reasoning over RulesConference on Empirical Methods in Natural Language Processing (EMNLP)Swarnadeep Saha, Sayan Ghosh, Shashank Srivastava, et al.2020 · 103 citations
13. Leap-Of-Thought: Teaching Pre-Trained Models to Systematically Reason Over Implicit KnowledgearXiv:2006.06609Alon Talmor, Oyvind Tafjord, Peter Clark, et al.2020 · 98 citations
14. Investigating the Limitations of Transformers with Simple Arithmetic TasksarXiv:2102.13019Rodrigo Nogueira, Zhiying Jiang, Jimmy Lin2021 · 96 citations
15. Proof Artifact Co-training for Theorem Proving with Language ModelsarXiv:2102.06203Jesse Michael Han, Jason Rute, Yuhuai Wu, et al.2021 · 82 citations
16. LEGO-Prover: Neural Theorem Proving with Growing LibrariesarXiv:2310.00656Haiming Wang, Huajian Xin, Chuanyang Zheng, et al.2023 · 79 citations
17. NaturalProofs: Mathematical Theorem Proving in Natural LanguagearXiv:2104.01112Sean Welleck, Jiacheng Liu, Ronan Le Bras, et al.2021 · 76 citations
18. NaturalProver: Grounded Mathematical Proof Generation with Language ModelsConference on Neural Information Processing Systems (NeurIPS)Sean Welleck, Jiacheng Liu, Ximing Lu, et al.2022 · 62 citations
19. Large Language Models are In-Context Semantic Reasoners rather than Symbolic ReasonersarXiv:2305.14825Xiaojuan Tang, Zilong Zheng, Jiaqi Li, et al.2023 · 52 citations
20. Linear algebra with transformersarXiv:2112.01898François Charton2021 · 31 citations
21. Neuro-Symbolic Artificial Intelligence: Current TrendsarXiv:2105.05330Md Kamruzzaman Sarker, Lu Zhou, Aaron Eberhart, et al.2021 · 12 citations

72 more papers of our library cite it; they have no page here yet.

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