---
title: "Who cites Weiyang Liu — page 2 — 655 papers of our library"
description: "655 papers of the Elamur Research library cite the works of Weiyang Liu, found in their bibliographies · page 2 of 3 · 101–200; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/weiyang-liu/cited-by/page/2/"
---
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# Who cites Weiyang Liu

666 citations of their works from 655 papers of our library (of the 149,439 whose bibliographies we read) · 248 with a page here, the most cited first · page 2 of 3 · 101–200 · [← Weiyang Liu](https://md.research.elamur.ai/free/en/authors/weiyang-liu/)

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101. [**Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences arXiv:2404.03715**Corby Rosset, Ching-An Cheng, Arindam Mitra, et al.*2024 · 44 citations*](https://md.research.elamur.ai/free/en/papers/rosset-2024-direct-nash-optimization-teaching-language/)
102. **[Forward-Backward Reasoning in Large Language Models for Mathematical Verification](https://md.research.elamur.ai/free/en/papers/jiang-2024-forward-backward-reasoning-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weisen Jiang, Han Shi, Longhui Yu, et al.*2024 · 44 citations*
103. [**NVLM: Open Frontier-Class Multimodal LLMs arXiv:2409.11402**Wenliang Dai, Nayeon Lee, Boxin Wang, et al.*2024 · 44 citations*](https://md.research.elamur.ai/free/en/papers/dai-2024-nvlm-open-frontier-class-multimodal/)
104. **[Towards Thinking-Optimal Scaling of Test-Time Compute for LLM Reasoning](https://md.research.elamur.ai/free/en/papers/yang-2025-towards-thinking-optimal-scaling-test/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Wenkai Yang, Shuming Ma, Yankai Lin, et al.*2025 · 43 citations*
105. **[MuggleMath: Assessing the Impact of Query and Response Augmentation on Math Reasoning](https://md.research.elamur.ai/free/en/papers/li-2024-mugglemath-assessing-impact-query-response/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chengpeng Li, Zheng Yuan, Hongyi Yuan, et al.*2024 · 43 citations*
106. **[Multi-step Problem Solving Through a Verifier: An Empirical Analysis on Model-induced Process Supervision](https://md.research.elamur.ai/free/en/papers/wang-2024-multi-step-problem-solving-through/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zihan Wang, Yunxuan Li, Yuexin Wu, et al.*2024 · 43 citations*
107. **[Improve Vision Language Model Chain-of-thought Reasoning](https://md.research.elamur.ai/free/en/papers/zhang-2025-improve-vision-language-model-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruohong Zhang, Bowen Zhang, Yanghao Li, et al.*2025 · 42 citations*
108. [**MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations arXiv:2502.06453**Kaixuan Huang, Jiacheng Guo, Zihao Li, et al.*2025 · 42 citations*](https://md.research.elamur.ai/free/en/papers/huang-2025-math-perturb-benchmarking-llms-math/)
109. [**AgentInstruct: Toward Generative Teaching with Agentic Flows arXiv:2407.03502**Arindam Mitra, Luciano Del Corro, Guoqing Zheng, et al.*2024 · 42 citations*](https://md.research.elamur.ai/free/en/papers/mitra-2024-agentinstruct-toward-generative-teaching-agentic/)
110. [**Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling arXiv:2502.06703**Runze Liu, Junqi Gao, Jian Zhao, et al.*2025 · 41 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-1b-llm-surpass-405b-llm/)
111. [**DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models arXiv:2411.00836**Chengke Zou, Xingang Guo, Rui Yang, et al.*2024 · 41 citations*](https://md.research.elamur.ai/free/en/papers/zou-2024-dynamath-dynamic-visual-benchmark-evaluating/)
112. [**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/)
113. [**InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output arXiv:2407.03320**Pan Zhang, Xiaoyi Dong, Yuhang Zang, et al.*2024 · 39 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-internlm-xcomposer-2-5/)
114. **[AceMath: Advancing Frontier Math Reasoning with Post-Training and Reward Modeling](https://md.research.elamur.ai/free/en/papers/liu-2025-acemath-advancing-frontier-math-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zihan Liu, Yang Chen, Mohammad Shoeybi, et al.*2025 · 37 citations*
115. [**Efficient Reasoning Models: A Survey arXiv:2504.10903**Sicheng Feng, Gongfan Fang, Xinyin Ma, et al.*2025 · 37 citations*](https://md.research.elamur.ai/free/en/papers/feng-2025-efficient-reasoning-models-survey/)
116. [**RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems? arXiv:2501.11284**Haotian Xu, Xing Wu, Weinong Wang, et al.*2025 · 37 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-redstar-scaling-long-cot-data/)
117. **[SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2024-sciinstruct-self-reflective-instruction-annotated/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Dan Zhang, Ziniu Hu, Sining Zhoubian, et al.*2024 · 37 citations*
118. [**Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning arXiv:2402.05808**Zhiheng Xi, Wenxiang Chen, Boyang Hong, et al.*2024 · 36 citations*](https://md.research.elamur.ai/free/en/papers/xi-2024-training-large-language-models-reasoning/)
119. [**MR-GSM8K: A Meta-Reasoning Benchmark for Large Language Model Evaluation arXiv:2312.17080**Zhongshen Zeng, Pengguang Chen, Shu Liu, et al.*2023 · 36 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2023-mr-gsm8k-meta-reasoning-benchmark/)
120. **[AbstentionBench: Reasoning LLMs Fail on Unanswerable Questions](https://md.research.elamur.ai/free/en/papers/kirichenko-2025-abstentionbench-reasoning-llms-fail-unanswerable/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Polina Kirichenko, Mark Ibrahim, Kamalika Chaudhuri, et al.*2025 · 35 citations*
121. **[MasRouter: Learning to Route LLMs for Multi-Agent Systems](https://md.research.elamur.ai/free/en/papers/yue-2025-masrouter-learning-route-llms-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yanwei Yue, Guibin Zhang, Boyang Liu, et al.*2025 · 35 citations*
122. [**On the Diversity of Synthetic Data and its Impact on Training Large Language Models arXiv:2410.15226**Hao Chen, Abdul Waheed, Xiang Li, et al.*2024 · 35 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-diversity-synthetic-data-impact-training/)
123. **[mCoT: Multilingual Instruction Tuning for Reasoning Consistency in Language Models](https://md.research.elamur.ai/free/en/papers/lai-2024-mcot-multilingual-instruction-tuning-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Huiyuan Lai, Malvina Nissim*2024 · 34 citations*
124. [**FormalMATH: Benchmarking Formal Mathematical Reasoning of Large Language Models arXiv:2505.02735**Zhouliang Yu, Ruotian Peng, Keyi Ding, et al.*2025 · 31 citations*](https://md.research.elamur.ai/free/en/papers/yu-2025-formalmath-benchmarking-formal-mathematical-reasoning/)
125. **[Learning Planning-based Reasoning by Trajectories Collection and Process Reward Synthesizing](https://md.research.elamur.ai/free/en/papers/jiao-2024-learning-planning-based-reasoning-trajectories/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Fangkai Jiao, Chengwei Qin, Zhengyuan Liu, et al.*2024 · 31 citations*
126. [**ChatGLM-Math: Improving Math Problem-Solving in Large Language Models with a Self-Critique Pipeline arXiv:2404.02893**Yifan Xu, Xiao Liu, Xinghan Liu, et al.*2024 · 30 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-chatglm-math-improving-math/)
127. [**Language Models as Science Tutors arXiv:2402.11111**Alexis Chevalier, Jiayi Geng, Alexander Wettig, et al.*2024 · 30 citations*](https://md.research.elamur.ai/free/en/papers/chevalier-2024-language-models-science-tutors/)
128. **[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*
129. [**InftyThink: Breaking the Length Limits of Long-Context Reasoning in Large Language Models arXiv:2503.06692**Yuchen Yan, Yongliang Shen, Yang Liu, et al.*2025 · 29 citations*](https://md.research.elamur.ai/free/en/papers/yan-2025-inftythink-breaking-length-limits-long/)
130. **[Towards Effective and Efficient Continual Pre-training of Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-effective-efficient-continual-pre-training/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jie Chen, Zhipeng Chen, Jiapeng Wang, et al.*2025 · 29 citations*
131. **[JiuZhang3.0: Efficiently Improving Mathematical Reasoning by Training Small Data Synthesis Models](https://md.research.elamur.ai/free/en/papers/zhou-2024-jiuzhang3-0-efficiently-improving-mathematical/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Kun Zhou, Beichen Zhang, Jiapeng Wang, et al.*2024 · 29 citations*
132. **[LangBridge: Multilingual Reasoning Without Multilingual Supervision](https://md.research.elamur.ai/free/en/papers/yoon-2024-langbridge-multilingual-reasoning-without-multilingual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dongkeun Yoon, Joel Jang, Sungdong Kim, et al.*2024 · 29 citations*
133. [**T1: Advancing Language Model Reasoning through Reinforcement Learning and Inference Scaling arXiv:2501.11651**Zhenyu Hou, Xin Lv, Rui Lu, et al.*2025 · 28 citations*](https://md.research.elamur.ai/free/en/papers/hou-2025-t1-advancing-language-model-reasoning/)
134. **[Automatic Instruction Evolving for Large Language Models](https://md.research.elamur.ai/free/en/papers/zeng-2024-automatic-instruction-evolving-large-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Weihao Zeng, Can Xu, Yingxiu Zhao, et al.*2024 · 28 citations*
135. [**Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning arXiv:2512.20848**NVIDIA: Aaron Blakeman, Aaron Grattafiori, Aarti Basant, et al.*2025 · 27 citations*](https://md.research.elamur.ai/free/en/papers/blakeman-2025-nemotron-3-nano-open-efficient/)
136. [**Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling arXiv:2408.16737**Hritik Bansal, Arian Hosseini, Rishabh Agarwal, et al.*2024 · 27 citations*](https://md.research.elamur.ai/free/en/papers/bansal-2024-smaller-weaker-yet-better-training/)
137. [**DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning arXiv:2310.02954**Jing Xiong, Zixuan Li, Chuanyang Zheng, et al.*2023 · 27 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2023-dq-lore-dual-queries-low/)
138. **[A Survey on Large Language Models for Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2025-survey-large-language-models-mathematical/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Peng-Yuan Wang, Tian-Shuo Liu, Chenyang Wang, et al.*2025 · 26 citations*
139. **[NaturalReasoning: Reasoning in the Wild with 2.8M Challenging Questions](https://md.research.elamur.ai/free/en/papers/yuan-2025-naturalreasoning-reasoning-wild-2-8m/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Weizhe Yuan, Jane Yu, Song Jiang, et al.*2025 · 26 citations*
140. [**Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of LLM Reasoning arXiv:2507.00432**Maggie Huan, Yuetai Li, Tuney Zheng, et al.*2025 · 25 citations*](https://md.research.elamur.ai/free/en/papers/huan-2025-math-reasoning-improve-general-llm/)
141. **[FuseChat: Knowledge Fusion of Chat Models](https://md.research.elamur.ai/free/en/papers/wan-2025-fusechat-knowledge-fusion-chat-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Fanqi Wan, Longguang Zhong, Ziyi Yang, et al.*2025 · 25 citations*
142. **[Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept Space](https://md.research.elamur.ai/free/en/papers/zhang-2025-soft-thinking-unlocking-reasoning-potential/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhen Zhang, Xuehai He, Weixiang Yan, et al.*2025 · 25 citations*
143. [**HunyuanProver: A Scalable Data Synthesis Framework and Guided Tree Search for Automated Theorem Proving arXiv:2412.20735**Yang Li, Dong Du, Linfeng Song, et al.*2024 · 25 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-hunyuanprover-scalable-data-synthesis/)
144. **[Chain-of-Reasoning: Towards Unified Mathematical Reasoning in Large Language Models via a Multi-Paradigm Perspective](https://md.research.elamur.ai/free/en/papers/yu-2025-chain-reasoning-unified-mathematical-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yiyao Yu, Yuxiang Zhang, Dongdong Zhang, et al.*2025 · 23 citations*
145. [**AI-Assisted Generation of Difficult Math Questions arXiv:2407.21009**Vedant Shah, Dingli Yu, Kaifeng Lyu, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/shah-2024-ai-assisted-generation-difficult-math/)
146. [**Step-Controlled DPO: Leveraging Stepwise Error for Enhanced Mathematical Reasoning arXiv:2407.00782**Zimu Lu, Aojun Zhou, Ke Wang, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-step-controlled-dpo-leveraging-stepwise/)
147. **[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*
148. **[MAgICoRe: Multi-Agent, Iterative, Coarse-to-Fine Refinement for Reasoning](https://md.research.elamur.ai/free/en/papers/chen-2025-magicore-multi-agent-iterative-coarse/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Justin Chen, Archiki Prasad, Swarnadeep Saha, et al.*2025 · 20 citations*
149. **[SLAM: Towards Efficient Multilingual Reasoning via Selective Language Alignment](https://md.research.elamur.ai/free/en/papers/fan-2025-slam-efficient-multilingual-reasoning-selective/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yuchun Fan, Yongyu Mu, YiLin Wang, et al.*2025 · 20 citations*
150. **[Code to Think, Think to Code: A Survey on Code-Enhanced Reasoning and Reasoning-Driven Code Intelligence in LLMs](https://md.research.elamur.ai/free/en/papers/yang-2025-code-think-think-code-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Dayu Yang, Tianyang Liu, Daoan Zhang, et al.*2025 · 19 citations*
151. **[A Survey of Post-Training Scaling in Large Language Models](https://md.research.elamur.ai/free/en/papers/lai-2025-survey-post-training-scaling-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanyu Lai, Xiao Liu, Junjie Gao, et al.*2025 · 18 citations*
152. **[R-PRM: Reasoning-Driven Process Reward Modeling](https://md.research.elamur.ai/free/en/papers/she-2025-r-prm-reasoning-driven-process/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shuaijie She, Junxiao Liu, Yifeng Liu, et al.*2025 · 18 citations*
153. [**Language Matters: How Do Multilingual Input and Reasoning Paths Affect Large Reasoning Models? arXiv:2505.17407**Zhi Rui Tam, Cheng-Kuang Wu, Yu Ying Chiu, et al.*2025 · 17 citations*](https://md.research.elamur.ai/free/en/papers/tam-2025-language-matters-multilingual-input-reasoning/)
154. **[Safe: Enhancing Mathematical Reasoning in Large Language Models via Retrospective Step-aware Formal Verification](https://md.research.elamur.ai/free/en/papers/liu-2025-safe-enhancing-mathematical-reasoning-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chengwu Liu, Ye Yuan, Yichun Yin, et al.*2025 · 17 citations*
155. **[STaR-SQL: Self-Taught Reasoner for Text-to-SQL](https://md.research.elamur.ai/free/en/papers/he-2025-star-sql-self-taught-reasoner/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingqian He, Yongliang Shen, Wenqi Zhang, et al.*2025 · 17 citations*
156. [**Entropy-Regularized Process Reward Model arXiv:2412.11006**Hanning Zhang, Pengcheng Wang, Shizhe Diao, et al.*2024 · 17 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-entropy-regularized-process-reward-model/)
157. **[Let the Expert Stick to His Last: Expert-Specialized Fine-Tuning for Sparse Architectural Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-let-expert-stick-his/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zihan Wang, Deli Chen, Damai Dai, et al.*2024 · 17 citations*
158. **[MuMath-Code: Combining Tool-Use Large Language Models with Multi-perspective Data Augmentation for Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/yin-2024-mumath-code-combining-tool-use/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shuo Yin, Weihao You, Zhilong Ji, et al.*2024 · 17 citations*
159. [**Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models arXiv:2412.02980**Alex Havrilla, Andrew Dai, Laura O'Mahony, et al.*2024 · 17 citations*](https://md.research.elamur.ai/free/en/papers/havrilla-2024-surveying-effects-quality-diversity-complexity/)
160. [**Can Large Reasoning Models Self-Train? arXiv:2505.21444**Sheikh Shafayat, Fahim Tajwar, Ruslan Salakhutdinov, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/shafayat-2025-large-reasoning-models-self-train/)
161. [**MathChat: Benchmarking Mathematical Reasoning and Instruction Following in Multi-Turn Interactions arXiv:2405.19444**Zhenwen Liang, Dian Yu, Wenhao Yu, et al.*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/liang-2024-mathchat-benchmarking-mathematical-reasoning-instruction/)
162. **[Language Models Encode the Value of Numbers Linearly](https://md.research.elamur.ai/free/en/papers/zhu-2025-language-models-encode-value-numbers/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Fangwei Zhu, Damai Dai, Zhifang Sui*2025 · 15 citations*
163. [**Preference Optimization for Reasoning with Pseudo Feedback arXiv:2411.16345**Fangkai Jiao, Geyang Guo, Xingxing Zhang, et al.*2024 · 15 citations*](https://md.research.elamur.ai/free/en/papers/jiao-2024-preference-optimization-reasoning-pseudo-feedback/)
164. **[Neuro-Symbolic Data Generation for Math Reasoning](https://md.research.elamur.ai/free/en/papers/li-2024-neuro-symbolic-data-generation-math/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zenan Li, Zhi Zhou, Yuan Yao, et al.*2024 · 14 citations*
165. [**Skywork-Math: Data Scaling Laws for Mathematical Reasoning in Large Language Models — The Story Goes On arXiv:2407.08348**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/)
166. [**Understanding Chain-of-Thought in LLMs through Information Theory arXiv:2411.11984**Jean-Francois Ton, Muhammad Faaiz Taufiq, Yang Liu*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/ton-2024-understanding-chain-thought-llms-through/)
167. [**Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive Search arXiv:2502.02508**Maohao Shen, Guangtao Zeng, Zhenting Qi, et al.*2025 · 13 citations*](https://md.research.elamur.ai/free/en/papers/shen-2025-satori-reinforcement-learning-chain-action/)
168. **[CriticLean: Critic-Guided Reinforcement Learning for Mathematical Formalization](https://md.research.elamur.ai/free/en/papers/peng-2026-criticlean-critic-guided-reinforcement-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhongyuan Peng, Yifan Yao, Kaijing Ma, et al.*2026 · 12 citations*
169. **[SKIntern: Internalizing Symbolic Knowledge for Distilling Better CoT Capabilities into Small Language Models](https://md.research.elamur.ai/free/en/papers/liao-2025-skintern-internalizing-symbolic-knowledge-distilling/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Huanxuan Liao, Shizhu He, Yupu Hao, et al.*2025 · 12 citations*
170. [**When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning arXiv:2504.01005**Nishad Singhi, Hritik Bansal, Arian Hosseini, et al.*2025 · 12 citations*](https://md.research.elamur.ai/free/en/papers/singhi-2025-solve-verify-compute-optimal-problem/)
171. [**Autoformalization in the Era of Large Language Models: A Survey arXiv:2505.23486**Ke Weng, Lun Du, Sirui Li, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/weng-2025-autoformalization-era-large-language-models/)
172. **[Layer-Aware Representation Filtering: Purifying Finetuning Data to Preserve LLM Safety Alignment](https://md.research.elamur.ai/free/en/papers/li-2025-layer-aware-representation-filtering-purifying/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hao Li, Lijun Li, Zhenghao Lu, et al.*2025 · 11 citations*
173. **[Learning from Diverse Reasoning Paths with Routing and Collaboration](https://md.research.elamur.ai/free/en/papers/lei-2025-learning-diverse-reasoning-paths-routing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhenyu Lei, Zhen Tan, Song Wang, et al.*2025 · 11 citations*
174. [**The Open Proof Corpus: A Large-Scale Study of LLM-Generated Mathematical Proofs arXiv:2506.21621**Jasper Dekoninck, Ivo Petrov, Kristian Minchev, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/dekoninck-2025-open-proof-corpus-large-scale/)
175. [**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/)
176. [**MIND: Math Informed syNthetic Dialogues for Pretraining LLMs arXiv:2410.12881**Syeda Nahida Akter, Shrimai Prabhumoye, John Kamalu, et al.*2024 · 11 citations*](https://md.research.elamur.ai/free/en/papers/akter-2024-mind-math-informed-synthetic-dialogues/)
177. **[FinChain: A Symbolic Benchmark for Verifiable Chain-of-Thought Financial Reasoning](https://md.research.elamur.ai/free/en/papers/xie-2026-finchain-symbolic-benchmark-verifiable-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhuohan Xie, Daniil Orel, Rushil Thareja, et al.*2026 · 10 citations*
178. [**Implicit Reasoning in Large Language Models: A Comprehensive Survey arXiv:2509.02350**Jindong Li, Yali Fu, Li Fan, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-implicit-reasoning-large-language-models/)
179. [**Leveraging Online Olympiad-Level Math Problems for LLMs Training and Contamination-Resistant Evaluation arXiv:2501.14275**Sadegh Mahdavi, Muchen Li, Kaiwen Liu, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/mahdavi-2025-leveraging-online-olympiad-level-math/)
180. **[MathFusion: Enhancing Mathematical Problem-solving of LLM through Instruction Fusion](https://md.research.elamur.ai/free/en/papers/pei-2025-mathfusion-enhancing-mathematical-problem-solving/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qizhi Pei, Lijun Wu, Zhuoshi Pan, et al.*2025 · 10 citations*
181. **[Progressive Multimodal Reasoning via Active Retrieval](https://md.research.elamur.ai/free/en/papers/dong-2025-progressive-multimodal-reasoning-active-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guanting Dong, Chenghao Zhang, Mengjie Deng, et al.*2025 · 10 citations*
182. [**Weight Ensembling Improves Reasoning in Language Models arXiv:2504.10478 · COLM 2025**Xingyu Dang, Christina Baek, Kaiyue Wen, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/dang-2025-weight-ensembling-improves-reasoning-language/)
183. [**MathGLM-Vision: Solving Mathematical Problems with Multi-Modal Large Language Model arXiv:2409.13729**Zhen Yang, Jinhao Chen, Zhengxiao Du, et al.*2024 · 10 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-mathglm-vision-solving-mathematical-problems/)
184. [**Progress or Regress? Self-Improvement Reversal in Post-training arXiv:2407.05013**Ting Wu, Xuefeng Li, Pengfei Liu*2024 · 10 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-progress-regress-self-improvement-reversal/)
185. [**Advancing Mathematical Reasoning in Language Models: The Impact of Problem-Solving Data, Data Synthesis Methods, and Training Stages arXiv:2501.14002**Zui Chen, Tianqiao Liu, Mi Tian, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-advancing-mathematical-reasoning-language-models/)
186. **[Examining False Positives under Inference Scaling for Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2025-examining-false-positives-under-inference/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yu Wang, Nan Yang, Liang Wang, et al.*2025 · 9 citations*
187. **[Theorem Prover as a Judge for Synthetic Data Generation](https://md.research.elamur.ai/free/en/papers/leang-2025-theorem-prover-as-judge-synthetic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Joshua Ong Jun Leang, Giwon Hong, Wenda Li, et al.*2025 · 9 citations*
188. **[To Code or not to Code? Adaptive Tool Integration for Math Language Models via Expectation-Maximization](https://md.research.elamur.ai/free/en/papers/wang-2025-code-or-not-code-adaptive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haozhe Wang, Long Li, Chao Qu, et al.*2025 · 9 citations*
189. [**Improving Physics Reasoning in Large Language Models Using Mixture of Refinement Agents arXiv:2412.00821**Raj Jaiswal, Dhruv Jain, Harsh Parimal Popat, et al.*2024 · 9 citations*](https://md.research.elamur.ai/free/en/papers/jaiswal-2024-improving-physics-reasoning-large-language/)
190. [**Search, Verify and Feedback: Towards Next Generation Post-training Paradigm of Foundation Models via Verifier Engineering arXiv:2411.11504**Xinyan Guan, Yanjiang Liu, Xinyu Lu, et al.*2024 · 9 citations*](https://md.research.elamur.ai/free/en/papers/guan-2024-search-verify-feedback-towards-next/)
191. [**Stable Code Technical Report arXiv:2404.01226**Nikhil Pinnaparaju, Reshinth Adithyan, Duy Phung, et al.*2024 · 9 citations*](https://md.research.elamur.ai/free/en/papers/pinnaparaju-2024-stable-code-technical-report/)
192. [**Brains vs. Bytes: Evaluating LLM Proficiency in Olympiad Mathematics arXiv:2504.01995**Hamed Mahdavi, Alireza Hashemi, Majid Daliri, et al.*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/mahdavi-2025-brains-vs-bytes-evaluating-llm/)
193. **[Exposing the Achilles' Heel: Evaluating LLMs Ability to Handle Mistakes in Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/singh-2025-exposing-achilles-heel-evaluating-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Joykirat Singh, Akshay Nambi, Vibhav Vineet*2025 · 8 citations*
194. **[FastMCTS: A Simple Sampling Strategy for Data Synthesis](https://md.research.elamur.ai/free/en/papers/li-2025-fastmcts-simple-sampling-strategy-data/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peiji Li, Kai Lv, Yunfan Shao, et al.*2025 · 8 citations*
195. [**ReForm: Reflective Autoformalization with Prospective Bounded Sequence Optimization arXiv:2510.24592**Guoxin Chen, Jing Wu, Xinjie Chen, et al.*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-reform-reflective-autoformalization-prospective-bounded/)
196. **[Superficial Self-Improved Reasoners Benefit from Model Merging](https://md.research.elamur.ai/free/en/papers/yuan-2025-superficial-self-improved-reasoners-benefit/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiangchi Yuan, Chunhui Zhang, Zheyuan Liu, et al.*2025 · 8 citations*
197. [**SIaM: Self-Improving Code-Assisted Mathematical Reasoning of Large Language Models arXiv:2408.15565**Dian Yu, Baolin Peng, Ye Tian, et al.*2024 · 8 citations*](https://md.research.elamur.ai/free/en/papers/yu-2024-siam-self-improving-code-assisted/)
198. **[Case2Code: Scalable Synthetic Data for Code Generation](https://md.research.elamur.ai/free/en/papers/shao-2025-case2code-scalable-synthetic-data-code/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yunfan Shao, Linyang Li, Yichuan Ma, et al.*2025 · 7 citations*
199. [**StepFun-Formalizer: Unlocking the Autoformalization Potential of LLMs through Knowledge-Reasoning Fusion arXiv:2508.04440**Yutong Wu, Di Huang, Ruosi Wan, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/wu-2025-stepfun-formalizer-unlocking-autoformalization/)
200. [**Autoformalizer with Tool Feedback arXiv:2510.06857**Qi Guo; Jianing Wang; Jianfei Zhang; Deyang Kong; Xiangzhou Huang; Xiangyu Xi; Wei Wang; Jingang Wang; Xunliang Cai; Shikun Zhang;, Wei Ye*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/guo-2025-autoformalizer-tool-feedback/)

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