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Who cites «LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning»

30 papers of our library cite it (of the 149,439 whose bibliographies we read) · 14 with a page here, the most cited first · ← back to «LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning»

  1. On the Opportunities and Risks of Foundation ModelsarXiv:2108.07258Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,160 citations
  2. Measuring Mathematical Problem Solving With the MATH DatasetarXiv:2103.03874Dan Hendrycks, Collin Burns, Saurav Kadavath, et al.2021 · 2,395 citations
  3. Proof Artifact Co-training for Theorem Proving with Language ModelsarXiv:2102.06203Jesse Michael Han, Jason Rute, Yuhuai Wu, et al.2021 · 82 citations
  4. NaturalProofs: Mathematical Theorem Proving in Natural LanguagearXiv:2104.01112Sean Welleck, Jiacheng Liu, Ronan Le Bras, et al.2021 · 76 citations
  5. Large Language Models as Analogical ReasonersarXiv:2310.01714Michihiro Yasunaga, Xinyun Chen, Yujia Li, et al.2023 · 74 citations
  6. Language Models Can Teach Themselves to Program BetterarXiv:2207.14502Patrick Haluptzok, Matthew Bowers, Adam Tauman Kalai2023 · 54 citations
  7. Lean-STaR: Learning to Interleave Thinking and ProvingarXiv:2407.10040Haohan Lin, Zhiqing Sun, Sean Welleck, et al.2024 · 51 citations
  8. A Survey on Deep Learning for Theorem ProvingarXiv:2404.09939Zhaoyu Li, Jialiang Sun, Logan Murphy, et al.2024 · 46 citations
  9. Through the Lens of Core Competency: Survey on Evaluation of Large Language ModelsarXiv:2308.07902Ziyu Zhuang, Qiguang Chen, Longxuan Ma, et al.2023 · 35 citations

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

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