---
title: "Who cites Talia Ringer — 96 papers of our library"
description: "96 papers of the Elamur Research library cite the works of Talia Ringer, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/talia-ringer/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/talia-ringer/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Talia Ringer](https://md.research.elamur.ai/free/en/authors/talia-ringer/) / cited by

# Who cites Talia Ringer

102 citations of their works from 96 papers of our library (of the 149,439 whose bibliographies we read) · 51 with a page here, the most cited first · [← Talia Ringer](https://md.research.elamur.ai/free/en/authors/talia-ringer/)

1. [**Llemma: An Open Language Model For Mathematics arXiv:2310.10631**Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, et al.*2023 · 286 citations*](https://md.research.elamur.ai/free/en/papers/azerbayev-2023-llemma-open-language-model-mathematics/)
2. **[LeanDojo: Theorem Proving with Retrieval-Augmented Language Models](https://md.research.elamur.ai/free/en/papers/yang-2023-leandojo-theorem-proving-retrieval-augmented/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Kaiyu Yang, Aidan M. Swope, Alex Gu, et al.*2023 · 253 citations*
3. [**Baldur: Whole-Proof Generation and Repair with Large Language Models arXiv:2303.04910**Emily First, Markus N. Rabe, Talia Ringer, et al.*2023 · 175 citations*](https://md.research.elamur.ai/free/en/papers/first-2023-baldur-whole-proof-generation-repair/)
4. **[When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs](https://md.research.elamur.ai/free/en/papers/kamoi-2024-when-can-llms-actually-correct/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ryo Kamoi, Yusen Zhang, Nan Zhang, et al.*2024 · 161 citations*
5. **[Automatically Correcting Large Language Models: Surveying the Landscape of Diverse Automated Correction Strategies](https://md.research.elamur.ai/free/en/papers/pan-2024-automatically-correcting-large-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Liangming Pan, Michael Saxon, Wenda Xu, et al.*2024 · 140 citations*
6. [**CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution arXiv:2401.03065**Alex Gu, Baptiste Rozière, Hugh Leather, et al.*2024 · 122 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-cruxeval-benchmark-code-reasoning-understanding/)
7. [**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/)
8. **[PutnamBench: Evaluating Neural Theorem-Provers on the Putnam Mathematical Competition](https://md.research.elamur.ai/free/en/papers/tsoukalas-2024-putnambench-evaluating-neural-theorem-provers/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**George Tsoukalas, Jasper Lee, John Jennings, et al.*2024 · 93 citations*
9. [**Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement Learning arXiv:2504.11354**Haiming Wang, Mert Unsal, Xiaohan Lin, et al.*2025 · 92 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-kimina-prover-preview-large-formal/)
10. [**Goedel-Prover: A Frontier Model for Open-Source Automated Theorem Proving arXiv:2502.07640**Yong Lin, Shange Tang, Bohan Lyu, et al.*2025 · 84 citations*](https://md.research.elamur.ai/free/en/papers/lin-2025-goedel-prover-frontier-model-open/)
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. [**Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-Correction arXiv:2508.03613**Yong Lin, Shange Tang, Bohan Lyu, et al.*2025 · 67 citations*](https://md.research.elamur.ai/free/en/papers/lin-2025-goedel-prover-v2-scaling-formal/)
13. [**What Algorithms can Transformers Learn? A Study in Length Generalization arXiv:2310.16028**Hattie Zhou, Arwen Bradley, Etai Littwin, et al.*2023 · 67 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-algorithms-transformers-learn-study-length/)
14. **[Verification and Refinement of Natural Language Explanations through LLM-Symbolic Theorem Proving](https://md.research.elamur.ai/free/en/papers/quan-2024-verification-refinement-natural-language-explanations/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xin Quan, Marco Valentino, Louise A. Dennis, et al.*2024 · 52 citations*
15. [**Lean-STaR: Learning to Interleave Thinking and Proving arXiv:2407.10040**Haohan Lin, Zhiqing Sun, Sean Welleck, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/lin-2024-lean-star-learning-interleave-thinking/)
16. [**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/)
17. [**An In-Context Learning Agent for Formal Theorem-Proving arXiv:2310.04353**Amitayush Thakur, George Tsoukalas, Yeming Wen, et al.*2023 · 47 citations*](https://md.research.elamur.ai/free/en/papers/thakur-2023-context-learning-agent-formal-theorem/)
18. [**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/)
19. [**Towards AI-Assisted Synthesis of Verified Dafny Methods arXiv:2402.00247**Md Rakib Hossain Misu, Cristina V. Lopes, Iris Ma, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/misu-2024-ai-assisted-synthesis-verified-dafny/)
20. [**Physics of Language Models: Part 1, Learning Hierarchical Language Structures arXiv:2305.13673**Zeyuan Allen-Zhu, Yuanzhi Li*2023 · 42 citations*](https://md.research.elamur.ai/free/en/papers/allen-zhu-2023-physics-language-models-part-1/)
21. [**Evaluating Language Models for Mathematics through Interactions arXiv:2306.01694**Katherine M. Collins, Albert Q. Jiang, Simon Frieder, et al.*2023 · 40 citations*](https://md.research.elamur.ai/free/en/papers/collins-2023-evaluating-language-models-mathematics-through/)
22. [**A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic Systems arXiv:2504.09037**Zixuan Ke, Fangkai Jiao, Yifei Ming, et al.*2025 · 39 citations*](https://md.research.elamur.ai/free/en/papers/ke-2025-survey-frontiers-llm-reasoning-inference/)
23. [**Lean Copilot: Large Language Models as Copilots for Theorem Proving in Lean arXiv:2404.12534**Peiyang Song, Kaiyu Yang, Anima Anandkumar*2024 · 39 citations*](https://md.research.elamur.ai/free/en/papers/song-2024-lean-copilot-large-language-models/)
24. **[BioCoder: A Benchmark for Bioinformatics Code Generation with Large Language Models](https://md.research.elamur.ai/free/en/papers/tang-2023-biocoder-benchmark-bioinformatics-code-generation/) [Bioinformatics](https://md.research.elamur.ai/free/en/venues/bioinformatics/)**Xiangru Tang, Bill Qian, Rick Gao, et al.*2023 · 38 citations*
25. **[Aristotle: IMO-level Automated Theorem Proving](https://md.research.elamur.ai/free/en/papers/achim-2025-aristotle-imo-level-automated-theorem/) [SuperIntelligence - Robotics - Safety & Alignment](https://md.research.elamur.ai/free/en/venues/superintelligence-robotics-safety-alignment/)**Tudor Achim, Alex Best, Alberto Bietti, et al.*2025 · 29 citations*
26. [**Decomposing the Enigma: Subgoal-based Demonstration Learning for Formal Theorem Proving arXiv:2305.16366**Xueliang Zhao, Wenda Li, Lingpeng Kong*2023 · 29 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-decomposing-enigma-subgoal-based-demonstration/)
27. **[AutoVerus: Automated Proof Generation for Rust Code](https://md.research.elamur.ai/free/en/papers/yang-2024-autoverus-automated-proof-generation-rust/) [Proceedings of the ACM on Programming Languages](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-acm-on-programming-languages/)**Chenyuan Yang, Xuheng Li, Md Rakib Hossain Misu, et al.*2024 · 28 citations*
28. [**Autoformalizing Euclidean Geometry arXiv:2405.17216**Logan Murphy, Kaiyu Yang, Jialiang Sun, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/murphy-2024-autoformalizing-euclidean-geometry/)
29. [**LEAN-GitHub: Compiling GitHub LEAN repositories for a versatile LEAN prover arXiv:2407.17227**Zijian Wu, Jiayu Wang, Dahua Lin, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-lean-github-compiling-github-lean/)
30. [**LLMSTEP: LLM proofstep suggestions in Lean arXiv:2310.18457**Sean Welleck, Rahul Saha*2023 · 22 citations*](https://md.research.elamur.ai/free/en/papers/welleck-2023-llmstep-llm-proofstep-suggestions-lean/)
31. **[AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://md.research.elamur.ai/free/en/papers/chen-2025-ai4research-survey-artificial-intelligence/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Mingda Yang, Libo Qin, et al.*2025 · 21 citations*
32. [**The Limits of Inference Scaling Through Resampling arXiv:2411.17501**Benedikt Stroebl, Sayash Kapoor, Arvind Narayanan*2024 · 21 citations*](https://md.research.elamur.ai/free/en/papers/stroebl-2024-limits-inference-scaling-through-resampling/)
33. [**Graph2Tac: Online Representation Learning of Formal Math Concepts arXiv:2401.02949**Lasse Blaauwbroek, Miroslav Olšák, Jason Rute, et al.*2024 · 19 citations*](https://md.research.elamur.ai/free/en/papers/blaauwbroek-2024-graph2tac-online-representation-learning-formal/)
34. **[Proving Theorems Recursively](https://md.research.elamur.ai/free/en/papers/wang-2024-proving-theorems-recursively/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Haiming Wang, Huajian Xin, Zhengying Liu, et al.*2024 · 19 citations*
35. [**MA-LoT: Model-Collaboration Lean-based Long Chain-of-Thought Reasoning enhances Formal Theorem Proving arXiv:2503.03205**Ruida Wang, Rui Pan, Yuxin Li, et al.*2025 · 18 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-ma-lot-model-collaboration-lean/)
36. [**miniCTX: Neural Theorem Proving with (Long-)Contexts arXiv:2408.03350**Jiewen Hu, Thomas Zhu, Sean Welleck*2024 · 18 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-minictx-neural-theorem-proving-long/)
37. **[APOLLO: Automated LLM and Lean Collaboration for Advanced Formal Reasoning](https://md.research.elamur.ai/free/en/papers/ospanov-2025-apollo-automated-llm-lean-collaboration/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Azim Ospanov, Farzan Farnia, Roozbeh Yousefzadeh*2025 · 17 citations*
38. [**Can Transformers Learn to Solve Problems Recursively? arXiv:2305.14699**Shizhuo Dylan Zhang, Curt Tigges, Stella Biderman, et al.*2023 · 17 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-transformers-learn-solve-problems-recursively/)
39. [**Solving Formal Math Problems by Decomposition and Iterative Reflection arXiv:2507.15225**Yichi Zhou, Jianqiu Zhao, Yongxin Zhang, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2025-solving-formal-math-problems-decomposition/)
40. [**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/)
41. [**AlphaVerus: Bootstrapping Formally Verified Code Generation through Self-Improving Translation and Treefinement arXiv:2412.06176**Pranjal Aggarwal, Bryan Parno, Sean Welleck*2024 · 11 citations*](https://md.research.elamur.ai/free/en/papers/aggarwal-2024-alphaverus-bootstrapping-formally-verified-code/)
42. **[Consistent Autoformalization for Constructing Mathematical Libraries](https://md.research.elamur.ai/free/en/papers/zhang-2024-consistent-autoformalization-constructing-mathematical-libraries/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Lan Zhang, Xin Quan, Andre Freitas*2024 · 11 citations*
43. [**Lemur: Integrating Large Language Models in Automated Program Verification arXiv:2310.04870**Haoze Wu, Clark Barrett, Nina Narodytska*2024 · 11 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-lemur-integrating-large-language-models/)
44. [**SubgoalXL: Subgoal-based Expert Learning for Theorem Proving arXiv:2408.11172**Xueliang Zhao, Lin Zheng, Haige Bo, et al.*2024 · 10 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2024-subgoalxl-subgoal-based-expert-learning/)
45. **[Reviving DSP for Advanced Theorem Proving in the Era of Reasoning Models](https://md.research.elamur.ai/free/en/papers/cao-2025-reviving-dsp-advanced-theorem-proving/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Chenrui Cao, Liangcheng Song, Zenan Li, et al.*2025 · 7 citations*
46. [**A Lean Dataset for International Math Olympiad: Small Steps towards Writing Math Proofs for Hard Problems arXiv:2411.18872**Roozbeh Yousefzadeh, Xuenan Cao, Azim Ospanov*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/yousefzadeh-2024-lean-dataset-international-math-olympiad/)
47. [**Premise Selection for a Lean Hammer arXiv:2506.07477**Thomas Zhu, Joshua Clune, Jeremy Avigad, et al.*2025 · 5 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-premise-selection-lean-hammer/)
48. [**StepFun-Prover Preview: Let's Think and Verify Step by Step arXiv:2507.20199**Shijie Shang, Ruosi Wan, Yue Peng, et al.*2025 · 5 citations*](https://md.research.elamur.ai/free/en/papers/shang-2025-stepfun-prover-preview-let-s/)
49. [**ImProver: Agent-Based Automated Proof Optimization arXiv:2410.04753**Riyaz Ahuja, Jeremy Avigad, Prasad Tetali, et al.*2024 · 5 citations*](https://md.research.elamur.ai/free/en/papers/ahuja-2024-improver-agent-based-automated-proof/)
50. **[MPS-Prover: Advancing Stepwise Theorem Proving by Multi-Perspective Search and Data Curation](https://md.research.elamur.ai/free/en/papers/liang-2025-mps-prover-advancing-stepwise-theorem/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhenwen Liang, Linfeng Song, Yang Li, et al.*2025 · 4 citations*
51. **[CodeRise: Bootstrapping LLMs for Ultra Low-Resource Programming Languages via Progressive Self-Refinement Curriculum](https://md.research.elamur.ai/free/en/papers/wen-2026-coderise-bootstrapping-llms-ultra-low/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tengfei Wen, Xuanang Chen, Ben He, et al.*2026*

45 more citing papers of our library have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/authors/talia-ringer/) — Talia Ringer