---
title: "Computational Theory and Mathematics — papers, page 2"
description: "Computational Theory and Mathematics: 95 papers of the Elamur Research library · page 2 of 2 · 26–95, the most cited first — our summary of each, its…"
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---
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# 🧮 Computational Theory and Mathematics

95 papers · page 2 of 2 · 26–95 · the most cited first · [all shelves](https://md.research.elamur.ai/free/en/shelves/)

Computational Theory and Mathematics is a subfield of Computer Science in the OpenAlex classification of science. The topics most of its papers here are on: «Mathematics, Computing, and Information Processing», «semigroups and automata theory», «Formal Methods in Verification».

## Papers

[← prev](https://md.research.elamur.ai/free/en/shelves/computer-science/computational-theory-and-mathematics/) [1](https://md.research.elamur.ai/free/en/shelves/computer-science/computational-theory-and-mathematics/) **2**

26. [**On the Practical Computational Power of Finite Precision RNNs for Language Recognition**Gail Weiss, Yoav Goldberg, Eran Yahav*2018 · 310 citations*](https://md.research.elamur.ai/free/en/papers/weiss-2018-practical-computational-power-finite-precision/)
27. [**Hallucination is Inevitable: An Innate Limitation of Large Language Models**Ziwei Xu, Sanjay Jain, Mohan Kankanhalli*2024 · 309 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-hallucination-inevitable-innate-limitation-large/)
28. [**TIES-Merging: Resolving Interference When Merging Models**Prateek Yadav, Derek Tam, Leshem Choshen, et al.*2023 · 306 citations*](https://md.research.elamur.ai/free/en/papers/yadav-2023-ties-merging-resolving-interference-merging/)
29. [**MathPrompter: Mathematical Reasoning using Large Language Models**Shima Imani, Liang Du, Harsh Shrivastava*2023 · 297 citations*](https://md.research.elamur.ai/free/en/papers/imani-2023-mathprompter-mathematical-reasoning-large-language/)
30. [**MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning**Xiang Yue, Xingwei Qu, Ge Zhang, et al.*2023 · 288 citations*](https://md.research.elamur.ai/free/en/papers/yue-2023-mammoth-building-math-generalist-models/)
31. [**Analysing Mathematical Reasoning Abilities of Neural Models**David Saxton, Edward Grefenstette, Felix Hill, et al.*2019 · 282 citations*](https://md.research.elamur.ai/free/en/papers/saxton-2019-analysing-mathematical-reasoning-abilities-neural/)
32. [**Large Language Models for Mathematical Reasoning: Progresses and Challenges**Janice Ahn, Rishu Verma, Renze Lou, et al.*2024 · 279 citations*](https://md.research.elamur.ai/free/en/papers/ahn-2024-large-language-models-mathematical-reasoning/)
33. [**Llemma: An Open Language Model For Mathematics**Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, et al.*2023 · 275 citations*](https://md.research.elamur.ai/free/en/papers/azerbayev-2023-llemma-open-language-model-mathematics/)
34. [**GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models**Iman Mirzadeh, Keivan Alizadeh, Hooman Shahrokhi, et al.*2024 · 262 citations*](https://md.research.elamur.ai/free/en/papers/mirzadeh-2024-gsm-symbolic-understanding-limitations-mathematical/)
35. [**MiniF2F: a cross-system benchmark for formal Olympiad-level mathematics**Kunhao Zheng, Jesse Michael Han, Stanislas Polu*2021 · 254 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2021-minif2f-cross-system-benchmark-formal/)
36. [**Scaling Relationship on Learning Mathematical Reasoning with Large Language Models**Zheng Yuan, Hongyi Yuan, Chengpeng Li, et al.*2023 · 252 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2023-scaling-relationship-learning-mathematical-reasoning/)
37. [**LeanDojo: Theorem Proving with Retrieval-Augmented Language Models**Kaiyu Yang, Aidan M. Swope, Alex Gu, et al.*2023 · 248 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-leandojo-theorem-proving-retrieval-augmented/)
38. [**Generative Language Modeling for Automated Theorem Proving**Stanislas Polu, Ilya Sutskever*2020 · 235 citations*](https://md.research.elamur.ai/free/en/papers/polu-2020-generative-language-modeling-automated-theorem/)
39. [**MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?**Renrui Zhang, Dongzhi Jiang, Yichi Zhang, et al.*2024 · 231 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-mathverse-multi-modal-llm-truly/)
40. [**ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving**Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.*2023 · 222 citations*](https://md.research.elamur.ai/free/en/papers/gou-2023-tora-tool-integrated-reasoning-agent/)
41. [**Accelerating scientific discovery with Co-Scientist**Juraj Gottweis, Wei-Hung Weng, Alexander Daryin, et al.*2025 · 212 citations*](https://md.research.elamur.ai/free/en/papers/gottweis-2025-accelerating-scientific-discovery-co/)
42. [**Efficient Parsing of Highly Ambiguous Context-Free Grammars with Bit Vectors**Helmut Schmid*2004 · 209 citations*](https://md.research.elamur.ai/free/en/papers/schmid-2004-efficient-parsing-highly-ambiguous-context/)
43. [**Progress measures for grokking via mechanistic interpretability**Neel Nanda, Lawrence Chan, Tom Lieberum, et al.*2023 · 207 citations*](https://md.research.elamur.ai/free/en/papers/nanda-2023-progress-measures-grokking-mechanistic-interpretability/)
44. [**Autoformalization with Large Language Models**Yuhuai Wu, Albert Q. Jiang, Wenda Li, et al.*2022 · 202 citations*](https://md.research.elamur.ai/free/en/papers/wu-2022-autoformalization-large-language-models/)
45. [**Measuring Multimodal Mathematical Reasoning with MATH-Vision Dataset**Ke Wang, Junting Pan, Weikang Shi, et al.*2024 · 198 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-measuring-multimodal-mathematical-reasoning-math/)
46. [**Learning To Use Formulas To Solve Simple Arithmetic Problems**Arindam Mitra, Chitta Baral*2016 · 178 citations*](https://md.research.elamur.ai/free/en/papers/mitra-2016-learning-use-formulas-solve-simple/)
47. [**Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs**Albert Q. Jiang, Sean Welleck, Jin Peng Zhou, et al.*2022 · 175 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2022-draft-sketch-prove-guiding-formal/)
48. [**Assessing the Reliability of Statistical Software: Part I**B. D. McCullough*1998 · 165 citations*](https://md.research.elamur.ai/free/en/papers/mccullough-1998-assessing-reliability-statistical-software/)
49. [**Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models**Bofei Gao, Feifan Song, Zhe Yang, et al.*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/gao-2024-omni-math-universal-olympiad-level/)
50. [**TheoremQA: A Theorem-driven Question Answering Dataset**Wenhu Chen, Ming Yin, Max Ku, et al.*2023 · 154 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-theoremqa-theorem-driven-question-answering/)
51. [**Computation of the Probability of Initial Substring Generation by Stochastic Context-Free Grammars**Frederick Jelinek, John D. Lafferty*1991 · 150 citations*](https://md.research.elamur.ai/free/en/papers/jelinek-1991-computation-probability-initial-substring-generation/)
52. [**HyperTree Proof Search for Neural Theorem Proving**Guillaume Lample, Marie-Anne Lachaux, Thibaut Lavril, et al.*2022 · 149 citations*](https://md.research.elamur.ai/free/en/papers/lample-2022-hypertree-proof-search-neural-theorem/)
53. [**rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking**Xinyu Guan, Li Lyna Zhang, Yifei Liu, et al.*2025 · 146 citations*](https://md.research.elamur.ai/free/en/papers/guan-2025-rstar-math-small-llms-can/)
54. [**Statistical Properties of Probabilistic Context-Free Grammars**Zhiyi Chi*1999 · 145 citations*](https://md.research.elamur.ai/free/en/papers/chi-1999-statistical-properties-probabilistic-context-free/)
55. [**Mapping to Declarative Knowledge for Word Problem Solving**Subhro Roy, Dan Roth*2018 · 143 citations*](https://md.research.elamur.ai/free/en/papers/roy-2018-mapping-declarative-knowledge-word-problem/)
56. [**ProofNet: Autoformalizing and Formally Proving Undergraduate-Level Mathematics**Zhangir Azerbayev, Bartosz Piotrowski, Hailey Schoelkopf, et al.*2023 · 141 citations*](https://md.research.elamur.ai/free/en/papers/azerbayev-2023-proofnet-autoformalizing-formally-proving-undergraduate/)
57. [**Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning**Pan Lu, Ran Gong, Shibiao Jiang, et al.*2021 · 134 citations*](https://md.research.elamur.ai/free/en/papers/lu-2021-inter-gps-interpretable-geometry-problem/)
58. [**Formal Mathematics Statement Curriculum Learning**Stanislas Polu, Jesse Michael Han, Kunhao Zheng, et al.*2022 · 132 citations*](https://md.research.elamur.ai/free/en/papers/polu-2022-formal-mathematics-statement-curriculum-learning/)
59. [**Unit Dependency Graph and its Application to Arithmetic Word Problem Solving**Subhro Roy, Dan Roth*2017 · 130 citations*](https://md.research.elamur.ai/free/en/papers/roy-2017-unit-dependency-graph-arithmetic/)
60. [**Deductive Verification of Chain-of-Thought Reasoning**Zhan Ling, Yunhao Fang, Xuanlin Li, et al.*2023 · 128 citations*](https://md.research.elamur.ai/free/en/papers/ling-2023-deductive-verification-chain-thought-reasoning/)
61. [**OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text**Keiran Paster, Marco Dos Santos, Zhangir Azerbayev, et al.*2023 · 124 citations*](https://md.research.elamur.ai/free/en/papers/paster-2023-openwebmath-open-dataset-high-quality/)
62. [**DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition**Z. Z. Ren, Zhihong Shao, Junxiao Song, et al.*2025 · 120 citations*](https://md.research.elamur.ai/free/en/papers/ren-2025-deepseek-prover-v2-advancing-formal/)
63. [**AlphaMath Almost Zero: Process Supervision without Process**Guoxin Chen, Minpeng Liao, Chengxi Li, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-alphamath-almost-zero-process-supervision/)
64. [**I-BERT: Integer-only BERT Quantization**Sehoon Kim, Amir Gholami, Zhewei Yao, et al.*2021 · 118 citations*](https://md.research.elamur.ai/free/en/papers/kim-2021-i-bert-integer-only-bert/)
65. [**ProcessBench: Identifying Process Errors in Mathematical Reasoning**Chujie Zheng, Zhenru Zhang, Beichen Zhang, et al.*2025 · 116 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2025-processbench-identifying-process-errors-mathematical/)
66. [**DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search**Huajian Xin, Z. Z. Ren, Junxiao Song, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/xin-2024-deepseek-prover-v1-5-harnessing/)
67. [**DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data**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/)
68. [**Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification**Aojun Zhou, Ke Wang, Zimu Lu, et al.*2023 · 109 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-solving-challenging-math-word-problems/)
69. [**GSM-Plus: A Comprehensive Benchmark for Evaluating the Robustness of LLMs as Mathematical Problem Solvers**Qintong Li, Leyang Cui, Xueliang Zhao, et al.*2024 · 107 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-gsm-plus-comprehensive-benchmark-evaluating/)
70. [**Learning to Reason Deductively: Math Word Problem Solving as Complex Relation Extraction**Zhanming Jie, Jierui Li, Wei Lu*2022 · 102 citations*](https://md.research.elamur.ai/free/en/papers/jie-2022-learning-reason-deductively-math-word/)
71. [**MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning**Ke Wang, Houxing Ren, Aojun Zhou, et al.*2023 · 98 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-mathcoder-seamless-code-integration-llms/)
72. [**Binarization of Synchronous Context-Free Grammars**Liang Huang, Hao Zhang, Daniel Gildea, et al.*2009 · 84 citations*](https://md.research.elamur.ai/free/en/papers/huang-2009-binarization-synchronous-context-free-grammars/)
73. [**Why Synchronous Tree Substitution Grammars?**Andreas Maletti*2010 · 38 citations*](https://md.research.elamur.ai/free/en/papers/maletti-2010-why-synchronous-tree-substitution-grammars/)
74. [**BabyFST - Towards a Finite-State Based Computational Model of Ancient Babylonian**Aleksi Sahala, Miikka Silfverberg, Antti Arppe, et al.*2020 · 23 citations*](https://md.research.elamur.ai/free/en/papers/sahala-2020-babyfst-finite-state-based-computational/)
75. [**Inherently Reversible Grammars, Logic Programming and Computability**Marc Dymetman*1991 · 20 citations*](https://md.research.elamur.ai/free/en/papers/dymetman-1991-inherently-reversible-grammars-logic-programming/)
76. [**Multi-metric optimization for coreference: The UniTN / IITP / Essex submission to the 2011 CONLL Shared Task**Olga Uryupina, Sriparna Saha, Asif Ekbal, et al.*2011 · 18 citations*](https://md.research.elamur.ai/free/en/papers/uryupina-2011-multi-metric-optimization-coreference-unitn/)
77. [**ArMATH: a Dataset for Solving Arabic Math Word Problems**Reem Alghamdi, Zhenwen Liang, Xiangliang Zhang*2022 · 17 citations*](https://md.research.elamur.ai/free/en/papers/alghamdi-2022-armath-dataset-solving-arabic-math/)
78. [**A Tree Transducer Model for Synchronous Tree-Adjoining Grammars**Andreas Maletti*2010 · 15 citations*](https://md.research.elamur.ai/free/en/papers/maletti-2010-tree-transducer-model-synchronous-tree/)
79. [**Skywork-Math: Data Scaling Laws for Mathematical Reasoning in Large Language Models — The Story Goes On**Liang Zeng, Liangjun Zhong, Liang Zhao, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2024-skywork-math-data-scaling-laws/)
80. [**Dependency Tree Transformation with Tree Transducers**Felix Hennig, Arne Köhn*2017 · 14 citations*](https://md.research.elamur.ai/free/en/papers/hennig-2017-dependency-tree-transformation-tree-transducers/)
81. [**Revisiting Multi-Tape Automata for Semitic Morphological Analysis and Generation**Mans Hulden*2009 · 12 citations*](https://md.research.elamur.ai/free/en/papers/hulden-2009-revisiting-multi-tape-automata-semitic/)
82. [**Design of Arabic Diacritical Marks**Mohamed Hssini, Azzeddine Lazrek*2011 · 8 citations*](https://md.research.elamur.ai/free/en/papers/hssini-2011-design-arabic-diacritical-marks/)
83. [**Orthography Engineering in Grammatical Framework**Krasimir Angelov*2015 · 5 citations*](https://md.research.elamur.ai/free/en/papers/angelov-2015-orthography-engineering-grammatical-framework/)
84. [**Bimorphisms and synchronous grammars**Stuart M. Shieber*2014 · 5 citations*](https://md.research.elamur.ai/free/en/papers/shieber-2014-bimorphisms-synchronous-grammars/)
85. [**Using a New Nonlinear Gradient Method for Solving Large Scale Convex Optimization Problems with an Application on Arabic Medical Text**Jaafar Hammoud, Ali Eisa, Natalia Dobrenko, et al.*2021 · 2 citations*](https://md.research.elamur.ai/free/en/papers/hammoud-2021-using-new-nonlinear-gradient-method/)
86. [**Bridging the Culture Gap: A Framework for LLM-Driven Socio-Cultural Localization of Math Word Problems in Low-Resource Languages**Israel Abebe Azime, Tadesse Destaw Belay, Dietrich Klakow, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/azime-2026-bridging-culture-gap-framework-llm/)
87. [**Tensors over Semirings for Latent-Variable Weighted Logic Programs**Esma Balkir, Daniel Gildea, Shay B. Cohen*2020 · 1 citation*](https://md.research.elamur.ai/free/en/papers/balkir-2020-tensors-over-semirings-latent-variable/)
88. [**Efficient universal generation in a fragment of Optimality Theory**Paul Siewert*2026*](https://md.research.elamur.ai/free/en/papers/siewert-2026-efficient-universal-generation-fragment-optimality/)
89. [**Learning Process Interaction Through Simplex ISL Transducers**Chenli Wang, Adam Jardine*2026*](https://md.research.elamur.ai/free/en/papers/wang-2026-learning-process-interaction-through-simplex/)
90. [**Phonological Processes as Modal Transductions**Tatevik Yolyan, Jesse Comer*2026*](https://md.research.elamur.ai/free/en/papers/yolyan-2026-phonological-processes-as-modal-transductions/)
91. [**Time-for-Accuracy: Formalizing Chain-of-Thought as an Expansion of Logical Depth**Yue Wang, Zhi Zhang, Wang Xi, et al.*2026*](https://md.research.elamur.ai/free/en/papers/wang-2026-time-accuracy-formalizing-chain-thought/)
92. [**Difficulties in Handling Mathematical Expressions in Universal Dependencies**Lauren Levine*2023*](https://md.research.elamur.ai/free/en/papers/levine-2023-difficulties-handling-mathematical-expressions-universal/)
93. [**Generic Oracles for Structured Prediction**Christoph Teichmann, Antoine Venant*2021*](https://md.research.elamur.ai/free/en/papers/teichmann-2021-generic-oracles-structured-prediction/)
94. [**Selected Operations, Algorithms, and Applications of n-Tape Weighted Finite-State Machines**Andre Kempe*2009*](https://md.research.elamur.ai/free/en/papers/kempe-2011-selected-operations-algorithms-applications-n/)
95. [**Synchronous Grammars and Transducers: Good News and Bad News**Stuart Shieber*2007*](https://md.research.elamur.ai/free/en/papers/shieber-2007-synchronous-grammars-transducers-good-news/)

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